This session aims to explore how hydrology is taught and learned at university and in professional education. It will bring together experiences and perspectives on teaching methods, curriculum design, textbooks and educational resources, field and laboratory activities, digital and active-learning approaches, and the responsible use of artificial intelligence in education. Contributions will discuss successful practices as well as the challenges encountered in equipping future hydrologists with the skills required by a changing discipline.

The session consists of solicited presentations only, followed by a panel discussion, with the aim of encouraging exchange among educators and stimulating new ideas for the future of hydrology education.

This session pays tribute to Hannes Flühler - a scientific leader and mentor, and the 2004 EGU John Dalton Medalist. The session celebrates Hannes’s many contributions to soil physics and vadose zone hydrology. His creativity and optimism in addressing flow and transport processes in unsaturated porous media were always guided by the cautionary principle of “digging deeper”. Meaning that we must revert to physical fundamentals and question incomplete explanations to observations.
His approach is even more relevant today where artificial intelligence and computational capacity transform data analysis and modelling, enabling consideration of increasingly complex scenarios across hydrology, land-surface science, plant physiology and agronomy. Meanwhile, societal expectations concerning soil health, ecosystem resilience and food security create new demand for rigorous soil physics offering new opportunities, but also a risk that sophisticated computations may obscure fundamental gaps in understanding. An illustrative example of these contemporary challenges is taken from work of Hannes Flühler (Flühler et al., 1976). Field measurements of unsaturated hydraulic conductivity differ markedly from laboratory measurements and model predictions, which naturally raise questions about the transferability of hydraulic descriptions from laboratory to field conditions. The example motivates us to take a deeper look at the physical basis and applicability of our description of soil processes.
In the spirit of Hannes Flühler’s approach, we invite contributions that dig deeper into fundamental questions in soil physics and hydrology. We encourage early career scientists and students to submit their work to this session. We welcome experimental, theoretical and computational studies that investigate discrepancies between observations and predictions, examine how soil structure and moisture history affect flow and transport, and test the transferability of hydraulic descriptions across scales and changing environmental conditions.

Flühler, H., Germann, P., Richard, F., & Leuenberger, J. (1976). Bestimmung von hydraulischen Parametern für die Wasserhaushaltsuntersuchungen im natürlich gelagerten Boden. Ein Vergleich von Feld‐und Laboratoriumsmethoden. Zeitschrift für Pflanzenernährung und Bodenkunde, 139(3), 329-342.

Human and environmental health are threatened globally by the individual or joint impacts of legacy contaminants such as trace metals and emerging pollutants including pharmaceuticals, fluorinated compounds or micro- and nanoplastics, as well as pathogens including viruses and bacteria. Hydrometeorological extremes can further exacerbate human and environmental health impacts by altering contaminant and pathogen dynamics in the water cycle. While there is increasing understanding of the toxicological and ecotoxicological implications of exposures to these individual or combined stressors, mechanistic understanding of the hydrological processes controlling the (de-)activation of pathogens or contaminants as well as the environmental conditions that affect their toxicity are poorly understood.

Moreover, in our climate adaptation strategies to hydroclimatic extremes, the implications for ecosystem and human health are often overlooked or ignored. Hydrological science can contribute to better prepare society for One Health Challenges by understanding critical water systems and improving and designing appropriate solutions.

We therefore solicit contributions that specifically investigate hydrological controls on the fate, transport and exposure to pathogens and contaminants (from geogenic and agricultural sources, as well as legacy and emerging pollutants) across surface water and groundwater systems. We also invite presentations on the hydrological impacts on physical water quality parameters of health relevance such as water temperature and oxygen content.

This session integrates interdisciplinary innovations covering field and lab experimental as well as model-based approaches in order to improve understanding of the drivers of human and environmental health risks as well as technical and governance approaches for One Health solutions that cross traditional disciplinary boundaries.

In a world of decreasing global water availability and increasing demand, our ability to quantify current water resources, understand the global water cycle, and predict their future trajectories is of paramount importance for water, food, and energy. Mounting pressures in a changing climate and increasing extremes are exposing a widening gap between freshwater science and the information required for effective and equitable decision-making. Now more than ever, a comprehensive, internationally coordinated, and policy-relevant synthesis of the freshwater system across scales is needed to manage water and ensure sustainable resources for human and natural systems.

This session invites contributions that focus on challenges and opportunities in global freshwater science. We highlight emerging scientific and technological advances towards a unified global synthesis of the freshwater cycle—spanning precipitation, evapotranspiration, surface water, groundwater, the cryosphere, ecosystems, human use, and water quality—to reveal patterns and test hypotheses from catchment to global scales. We encourage innovative submissions that highlight integrative approaches—including both traditional and under-utilised observations (e.g., citizen science), reanalyses, process-based models, and emerging AI-enabled inference—to advance towards an improved understanding of global freshwater at unprecedented spatial and temporal resolution, and to enable a credible, routinely updated global assessment supporting discovery and actionable solutions.

The terrestrial water cycle is usually studied one compartment at a time: precipitation by meteorologists, runoff and recharge by hydrologists, aquifers by hydrogeologists, and evapotranspiration by land-surface scientists. Yet climate change, land-use change and human water use act mainly on the links between these compartments. They change how rainfall is partitioned at the surface, how much reaches aquifers and how long it is stored there, and how much returns to the atmosphere to fall again as rain.

This session invites studies that cross at least one of these boundaries. Relevant topics include precipitation extremes, monsoons and atmospheric rivers and their imprint on runoff and recharge; soil moisture, infiltration, and snow and glacier melt; groundwater recharge, surface water–groundwater exchange, and storage change from GRACE and in-situ networks; evapotranspiration, moisture recycling and irrigation feedbacks; and the carbon, solutes and pollutants that water carries along its flow paths, including greenhouse-gas emissions from reservoirs. We also welcome interventions that deliberately reconnect the loop, such as managed aquifer recharge and nature-based solutions. Methods that link compartments are equally welcome: isotopes and tracers, remote sensing, coupled and hybrid models, and explainable machine learning.

We particularly encourage work on water-balance closure across scales, studies from data-scarce and monsoon-dominated regions, and research that turns whole-cycle understanding into water-security decisions. Early-career scientists are strongly encouraged to submit.

Nature-based Solutions (NbS) are increasingly promoted as a key strategy for climate adaptation, aiming to improve sponge functioning by intercepting, slowing, storing, and slowly releasing water. By reducing flood peaks, enhancing drought resilience, and delivering ecosystem services such as improved water quality and biodiversity, NbS are central to climate-resilient land and water management. However, implementation at scale remains limited due to insufficient evidence on the (eco-)hydrological impacts of NbS across spatial and temporal scales, and limited translation of this knowledge into decision-making.
Key questions remain regarding how effectiveness evolves over time, how maintenance influences long-term outcomes, how impacts propagate across scales, under which conditions local interventions contribute to landscape-scale resilience, and how scientific evidence can support upscaling.
This session explores the role of quantitative assessment in understanding Nature-based Solutions (NbS) and supporting their upscaling. It examines how evidence from local monitoring and modelling to catchment-scale assessments can guide implementation, inform policy, and strengthen confidence in climate adaptation investments, advancing climate-resilient sponge landscapes. We welcome contributions that:
•Quantify the effectiveness of NbS for multiple objectives, including flood mitigation, drought resilience, and associated co-benefits, trade-offs, and uncertainties to inform design, implementation, prioritization, and upscaling.
•Investigate temporal and spatial scaling, including long-term performance, delayed benefits, degradation processes, maintenance requirements, and cumulative impacts from plot to catchment scales.
•Integrate monitoring, experimental, and modelling approaches to strengthen attribution, process understanding, and impact assessment of NbS, using observed evidence to validate models and evaluate the scaling of flood, drought, and eco-hydrological benefits.
•Highlight the qualitative and quantitative evidence required by local actors, implementers, policy-makers, and investors to support decision-making.
•Develop decision-support tools, indicators, and assessment frameworks that strengthen links between quantification, implementation, governance, financing, and policy.
•Demonstrate how evidence from monitoring and modelling has informed planning, policy development, implementation strategies, investment priorities, and the mainstreaming of NbS.

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.

Effective and enhanced hydrological monitoring is essential for understanding water-related processes in a rapidly changing world. Image-based river monitoring, remote and proximal sensing, low-cost and opportunistic sensors, citizen science and artificial intelligence are reshaping the way hydrological processes are observed across scales, environments and conditions. Yet the value of these innovations depends on methodological rigour: new observational approaches need to be critically evaluated, benchmarked against established methods and integrated with existing datasets before their contribution to process understanding, modelling and operational hydrology can be established.

This session is co-sponsored by MOXXI (Measurements and Observations in the XXI century), the IAHS working group on novel observational methods, and provides a forum for research in which observation itself is the subject of investigation. We invite contributions on:

• Disruptive and Innovative sensors and technologies in hydrology (e.g., UAS, camera systems – RGB, thermal, multispectral and hyperspectral – low-cost and open-hardware sensors, distributed fibre-optic sensing).
• Advancing opportunistic sensing strategies in hydrology (e.g., commercial microwave links, GNSS reflectometry, smartphones, personal weather stations).
• Automated and semi-automated methods for extracting hydrological variables (e.g., water level, flow velocity, discharge, turbidity, plastic transport and river health parameters), including image processing, machine learning, data fusion, and edge-computing.
• Critical evaluation, benchmarking and intercomparison of observational approaches, datasets and products, including calibration/validation and uncertainty quantification.
• Integration of novel and conventional observations, and new approaches to long-term hydrological monitoring.
• Innovative citizen science and crowd-based methods for monitoring hydrological extremes.
• Novel strategies to enhance the detail and accuracy of observations in remote areas or data-scarce contexts.
• Demonstrations of how novel observations advance process understanding, model development and operational practice.•

The goal of this session is to bring together scientists advancing hydrological monitoring, to foster a critical discussion on the reliability and added value of emerging observational approaches, and to explore how these innovations can be scaled up to larger applications.

Hydrological predictions - simulations or forecasts - are fundamentally uncertain. This has been recognized more than a century ago (see Krzysztofowicz, 2001, and references therein), and it is still true today. For a complete picture, hydrological predictions should therefore not only provide point estimates, but probabilistic statements. Such probabilistic predictions are not only an honest account of what we know (and what we do not know), they also provide practical advantages for end users and decisionmakers (Buizza, 2008). Nevertheless, and despite considerable progress, to date the majority of hydrological models still provide single-valued output. With this session, we want to establish a platform to promote the paradigm-shift towards making probabilistic predictions in hydrology the standard rather than the exception.
We welcome contributions from the following fields (but not limited to these):
- Theory and methodology for identifying and quantifying sources and pathways of uncertainty from data through models to predictions, including approaches based on probability theory and information theory
- Development of model architectures and efficient training procedures enabling fast, accurate and reliable probabilistic predictions, including physics-based, data-driven, machine-learning and hybrid approaches, stochastic parameterisations, ensemble prediction systems, and post-processing
- Probabilistic benchmarks and evaluation frameworks, including benchmark models and datasets, verification methods, scoring rules, calibration, and large-scale initiatives for assessing probabilistic hydrological predictions
- Operational implementations and real-world applications of probabilistic hydrological modelling, including flood forecasting, climate change impact assessment, and water resources management
- Development of strategies for effectively communicating probabilistic predictions to end users

References
Buizza, R. (2008), The value of probabilistic prediction. Atmosph. Sci. Lett., 9: 36-42. https://doi.org/10.1002/asl.170
Krzysztofowicz, R.: The case for probabilistic forecasting in hydrology, Journal of Hydrology, 249, 2-9, https://doi.org/10.1016/S0022-1694(01)00420-6, 2001.

Predictions of physical processes in aquifers, rivers and across compartments are strongly affected by uncertainties and errors in model structure, parameters and forcing data. Thus, reliable predictions at any scale (lab/field/catchment) require a rigorous and transparent treatment of these uncertainties, from parameter estimation to uncertainty quantification and model selection. Acknowledging uncertainties and equifinality as a fundamental part of modelling and understanding model-parameter interactions during calibration opens up otherwise-missed opportunities for scientific insight and decision support. This session is a platform for discussion of methodological advances and workflows addressing inverse problems in surface and subsurface hydrology, i.e., using available observed data to gain knowledge/ constrain uncertainty about related but unobserved quantities of interest. We invite contributions on improved concepts, approaches & computational algorithms (be they Bayesian, frequentist, optimization- or ML-based) as well as demonstrations of best practices, challenges & pitfalls, especially (but not exclusively) related to:

- parameter inference, model selection/ averaging, sensitivity and uncertainty analysis;
- representation of uncertain data and boundary conditions;
- integration of heterogeneous/multi-source data;
- identification and treatment of model-structural errors;
- distilling new model formulations (data-driven, physics-based, knowledge-guided or hybrid);
- data worth and optimal experimental design strategies toward maximum information/minimum uncertainty;
- constraint learning/ novel likelihood formulations to incorporate expert knowledge in inversion;
- other regularization strategies that help solve ill-posed problems;
- computational efficiency of solving inverse problems, including surrogate and ML-based techniques;
- Benchmarking and intercomparison efforts on synthetic or real-world, local or large-sample data-sets;
- transparent and reproducible workflows for robust predictions and visualization/communication of inference results to stakeholders;
- real-time inversion for operational forecasting;
- variations of all the above specific to low-dimensional, high-dimensional, dynamic, spatially distributed, geostatistical, linear, or non-linear inverse-problem settings.

Much has been written on how hydrological modelling can be improved: better data, better models, better objective functions, better benchmarking, better uncertainty quantification, better communication, and so forth. Yet, it remains rare to find definitions of what “better” means in each context, and even more to see such recommendations implemented comprehensively.

This session provides a platform to discuss which gaps remain between current and recommended model application, and how such gaps may be bridged. We welcome contributions under the following themes:

1. The theoretical underpinnings of models, centered around the question:
“How good are our models and the approaches we use to decide if they are, and how far can we stretch their applicability?”

2. The technical side of model application, centered around the question:
“How do we efficiently configure, parametrize and run our models?”

3. The social side of model application, centered around the question:
“Why do we use the tools we do, and how do we communicate their strengths and weaknesses?”

4. The future of model application, centered around our main question:
“Where are we today, and where do we want to be tomorrow?”

Contributions may include comparison of existing models and techniques, and development of more robust alternatives; as well as examples of studies that implement existing recommended practices throughout their modelling chain; and lessons from post-audits comparing past predictions with observed outcomes. We particularly invite abstracts that investigate whether model assumptions and representations are supported by evidence and whether models are fit for their intended purpose, and those that take a step back and assess the current state of hydrological modelling in comparison to what may, by now, be theoretically and practically possible.

Worldwide, disturbances modify the interactions and feedbacks among hydrologic, geomorphic, biogeochemical, and ecological systems, thereby reshaping the hydrological functioning of landscapes. Wildfires, deforestation, volcanic eruptions, earthquakes, and other disturbances alter water partitioning, flow paths, the transport of solutes and sediments. Although their immediate impacts may be spatially or temporally constrained, their hydrological consequences can persist and propagate across landscapes. This session explores how disturbances reshape hydrological processes across spatial and temporal scales, with particular interest in the mechanisms controlling the system response and recovery. We welcome observational, experimental, and modeling studies addressing individual, sequential, or interacting disturbances. We especially encourage contributions examining multiple or overlapping disturbances and their implications for predicting hydrological change and informing watershed and land management.

Low elevation coastal zones (LECZ, areas below 10 m above sea level) are among the most dynamic, densely populated, and intensively managed environments on Earth. They support major population centres, agricultural production, ecosystems and industries. At the same time, they are increasingly exposed to hazards due to accelerating global change, including sea-level rise, changing storm surge and precipitation regimes, heat waves, land subsidence and morphological changes of estuaries, deltas and open coasts.
These pressures create interconnected challenges for water management, infrastructure design and ecosystem stewardship, driving adaptation needs. LECZ are at the interface between terrestrial hydrology and marine dynamics, where flood protection, lowland drainage, freshwater availability, saltwater intrusion, nutrient loads, sediment transport and ecological functioning are governed by the interactions of catchment and coastal processes. However, scientific understanding, modelling approaches and management practices often treat landward and seaward processes separately. Taking a systems perspective is essential for assessing compound and multi-hazard risks, identifying adaptation options and supporting decision-making in LECZs.
This session welcomes contributions that improve system and process understanding, develop monitoring and modelling approaches and support decision making in LECZs across spatial and temporal scales, from local case studies to regional, continental, and global assessments. Contributions addressing data gaps and novel approaches for infrastructure design are encouraged.
We invite submissions on topics including, but not limited to:
i) Monitoring, understanding and characterising processes and hazards in LECZs
ii) Process-based, statistical, hybrid and data-driven modelling approaches for coastal catchment systems, water resources, compound and multi-hazard drivers, estuarine and deltaic dynamics and groundwater-surface-water-sea interactions.
iii) Tools and frameworks supporting integrated water management, infrastructure design and adaptation

Earth operates as a complex, self-regulating cybernetic system driven by both internal processes and external astronomical forcing. This session explores the intricate feedback loops between the Solar System’s gravitational dynamics and Earth’s interconnected geospheres—including the atmosphere, hydrosphere, lithosphere, biosphere, pedosphere, troposphere, magnetosphere, and ionosphere. We focus specifically on how these systemic interactions govern sub-system variations, with a core emphasis on water balance components and hydrological cycles.
To decipher these non-linear, multi-scale relationships, traditional deterministic models must be augmented with data-driven methodologies. We invite contributions that advance empirical research tasks, conceptual frameworks, and system-level models. We particularly welcome studies utilizing artificial intelligence (AI), statistical learning, machine learning, and advanced data-mining techniques to analyze observational and proxy datasets. By bridging planetary dynamics, cybernetic geoscience, and modern data science, this session aims to foster a holistic understanding of Earth’s systemic balance and improve our predictive capabilities in a changing cosmic and terrestrial environment.

Latin America is home to major hydrological systems in the world. The combination of diverse climates, biomes, and ecosystems with a rapidly growing human footprint makes Latin America a unique test bed for exploring hydrological knowledge at the interface of science, policy, and practice in water resources.

This session welcomes both theoretical and case study applications that consider observation and/or modelling to study hydrological processes and the possible effects of social and environmental changes on water resources systems. We will explore advances in hydrology at regional, national and continental scales in Latin America.

Aligned with the IAHS Scientific Decade HELPING (Hydrology Engaging Local People IN one Global world), we especially welcome contributions that: (1) investigate interactions of water resources across different spatial scales (2) provide holistic solutions for water security, (3) engages with hydrological knowledge co-creation.

We want to offer a platform to discuss how science could improve operational hydrology, how practical problems can inform important scientific questions, and the skills and tools necessary for translating hydrological research into operation and decision-making in the management of water resources systems of Latin America.

Advances in hydrological science and technology are transforming water resource management and mitigating water and food insecurity challenges that are being intensified by climate change across Africa. Emerging methods in artificial intelligence, machine learning, including foundation models and transfer-learning approaches for data-scarce basins, and digital innovations are being combined with process-based hydrological models. These approaches are improving provision of information on water availability, and enhancing early warnings of floods, droughts, and water stress. This session aims to bring together communities working on different strands of African hydrology, climate risks, environmental risks, and Water-Energy-Food-Ecosystem nexus. We invite contributions across three key areas: (1) understanding and monitoring hydrological processes, groundwater-surface water interactions, low-cost innovative measurement and monitoring systems, remote sensing and AI-driven modelling; (2) Prediction and assessment - drought/flood forecasting, seasonal to decadal forecasting, climate change impact assessments including compound and multi-hazard risks, and operational early warning systems for anticipatory action; and (3) Management and solutions - water resources management and climate change adaptation strategies. Studies that utilize interdisciplinary approaches are particularly encouraged. By fostering collaboration among researchers, practitioners, and policymakers, this session aims to bring to the forefront the advances in understanding African hydrology and climate while promoting practical solutions. Science-for-solutions initiatives contributing to the IAHS HELPING decade are welcome.

Understanding hydrological processes in drylands, from hyperarid to semi-arid regions, is a major research challenge, particularly under increasing pressure from climate change, land-use change, and water scarcity. These regions, which span over 40% of the Earth’s land surface and support more than two billion people, face complex hydrological challenges due to their high climatic variability. Their limited water resources are characterized by strong climatic variability, intermittent flows, and complex interactions between rainfall, soils, vegetation, surface runoff, and groundwater.

This session welcomes contributions that improve our understanding of key hydrological processes in drylands (such as semi-arid zones in the Mediterranean or hyperarid ones in the Sahara and other desertic areas), including rainfall variability, infiltration and runoff generation mechanisms, antecedent soil moisture controls, hydrological connectivity, transmission losses, evapotranspiration, and groundwater recharge. We particularly encourage studies addressing the episodic and threshold-driven nature of hydrological responses, surface–groundwater interactions, and the challenges of monitoring and modeling water fluxes across scales.

Given the scarcity of long-term observations in many dryland regions, notably in the Global South, we also welcome approaches combining field observations, remote sensing, novel monitoring techniques, citizen science, and modeling. Studies examining how climate and land-use changes may alter hydrological processes and water availability are especially encouraged.

By bringing together observational, experimental, and modeling perspectives, this session aims to improve process-based understanding of dryland hydrology and identify pathways towards more resilient water systems in dryland regions.

Reliable hydrological information is essential for water-resource management, disaster risk reduction, ecosystem protection, and climate adaptation. However, hydrological prediction remains challenging in many regions due to sparse monitoring networks, limited observations, and rapidly changing hydroclimatic conditions. Advances in Earth observation, artificial intelligence (AI), digital technologies, and computational methods are transforming the field, enabling a shift beyond traditional Prediction in Ungauged Basins (PUB) toward a broader concept of hydrological intelligence that integrates observations, process understanding, modelling, and data-driven approaches.

This session invites interdisciplinary contributions that advance hydrological prediction and intelligence in data-scarce and poorly monitored catchments. We welcome methodological, observational, and applied studies that improve predictive capability, transferability, interpretability, uncertainty characterisation, and operational utility.

Topics include hydrological prediction and forecasting, early-warning systems, regionalisation and transfer learning, AI and machine learning, foundation models, explainable and trustworthy AI, hybrid and physics-informed modelling, digital twins, data assimilation, model calibration, uncertainty analysis, climate-change impacts and adaptation, groundwater-surface water interactions, ecohydrology, socio-hydrology, citizen science, and open hydrological science.

Particular emphasis is placed on integrating Earth observation products, environmental data streams, and emerging computational techniques to improve prediction, enhance process understanding, and support decision-making under uncertainty. Contributions spanning local to global scales are encouraged.

By bringing together researchers from hydrology, hydro informatics, Earth observation, and environmental data science, the session aims to foster collaboration and accelerate the development of next-generation hydrological intelligence systems for robust prediction, adaptive water management, and climate resilience in an increasingly uncertain and data-constrained world.

Water in the snowpack and in glaciers represents an important component of the hydrological cycle in many regions of the world and is crucial to sustaining life during dry seasons. Predicted impacts of climate change in catchments with snow and/or glacier cover (i.e., shifts from snowfall to rainfall, modified total precipitation amounts, earlier snowmelt, and shrinking glacier cover) will affect water resources availability for environmental and anthropogenic uses at multiple scales, with implications for energy production, agriculture, drinking water provision, as well as for water water management and ecosystems.
Runoff generation in catchments that feature snow or ice profoundly differs from purely rainfed catchments. Yet, our knowledge of snow/ice accumulation and melt, meltwater flowpaths, meltwater contribution to runoff, and the evolution of these catchments' hydrological regime in a changing climate, remain highly uncertain. This is due to both limited availability and inherently high spatial variability of hydrological and meteorological data.

This session welcomes contributions on the following topics (but is not limited to these):
- Experimental research on the physical processes determining snow and ice melt runoff and their potential implementation in hydrological models;
- Development of novel strategies for snow and ice melt runoff modelling in diverse and/or changing climatic and land-cover conditions, including glacier retreat
- Evaluation of remote-sensing or in-situ snow products and application for snow and glacier melt runoff calibration, data assimilation, streamflow forecasting or quantification of the physical properties of snow and ice
- Studies exploring glacier and snow meltwater through stable water isotopes, including experimental investigations and development of isotope-enabled snow and hydrological models
- Studies addressing the impact of climate change and/or extreme events, e.g., droughts, on the water cycle of snow and glacier affected catchments
- Studies targeting snowpack, snowmelt, glacier, ice melt or runoff time series reconstruction or reanalysis over long periods to fill data gaps

Mountains are an essential component of the Earth system and are widely recognised as major sources of freshwater. Their water resources support communities and ecosystems within mountain regions and are also critical for social-ecological systems further downstream.

The strong heterogeneity in hydro-meteorological conditions arising from elevation gradients, complex topography, and geological conditions makes hydrological processes highly variable across space and time. Climate change and growing human pressures are altering these processes, highlighting the need to better understand the controls on water resources and related ecosystem services. Mountains are therefore unique sentinels of global change, providing a setting for detecting, understanding, and monitoring its effects.

This session brings together researchers working on mountain hydrology worldwide to share the latest findings, innovative approaches, and new perspectives. Emphasis will be placed on the role of mountain regions in the water cycle and in providing, storing, and regulating water resources, as well as on the challenges of observing and understanding hydrological change in these complex environments. We invite contributions addressing past, present, and future conditions, including changes driven by climate and land-use change, their impacts on mountain and downstream regions, and adaptation strategies to support the long-term sustainability of mountain ecosystem services. We particularly encourage contributions on technological and methodological innovations that help overcome observational challenges.

Topics of interest include, but are not limited to
- sources of information for assessing past and present conditions in mountain surface-water and groundwater systems;
- innovative observational approaches and emerging data sources for characterising hydrological processes in mountains and their spatio-temporal variability;
- modelling approaches for assessing, attributing, and projecting hydrological change;
- methods to identify and disentangle drivers of hydrological change;
- prediction, evolution, and impacts of hydrological extremes;
- case studies on adaptation to changes in availability of water resources and associated risks;
- integration of complementary sources of evidence and knowledge, including citizen science, Indigenous knowledge systems, and other approaches that improve understanding of mountain systems and support the sustainable management of water resources

Recent droughts in Europe (e.g. 2018 and 2022) have highlighted the vulnerability of temperate and subarctic regions to drought, and the threats it poses to ecosystems, agriculture, energy production, water resources and societies. However, much of the research body on drought focusses on hotter and drier regions, potentially under- or misrepresenting colder and wetter regions, and their complex behavior under droughts – including systems dominated by snow and glaciers to systems without, systems with shallow soils to systems with large groundwater bodies. This session aims to gather knowledge about droughts in cold- and temperate regions across the full chain from meteorological to hydrological drought, spanning water vapor, precipitation, soil moisture, streamflow, and groundwater. We especially welcome submissions related to the following topics:
1. Drought monitoring and forecasting, hereunder work related to drought indices, drought drivers and climate change
2. Drought impacts on society and ecosystems, including water resources, risk assessment, management, and governance.
3. Groundwater drought, including aquifer vulnerability, quality and quantity issues and anthropogenic impacts from abstraction and irrigation
4. Related hazards such as heatwaves and wildfires typical for cold- and temperate regions.

The Critical Zone (CZ), encompassing the Earth's surface from the top of the vegetation canopy to the bottom of the circulating groundwater, is essential for sustaining life and maintaining environmental health. Understanding this region of complex intersections within the natural world, and between the environment and society, requires a collaborative, multidisciplinary approach that transcends disciplinary and national boundaries, bridging gaps between short-term and long-term environmental processes. This session will highlight CZ science, CZ methodologies, and the collaborative efforts of CZ research sites and networks from around the world. Topics of interest include, but are not limited to: Innovative techniques in CZ research and monitoring, such as integrated observation and modeling approaches or hybrid methods; Advances in understanding soils, hydrology, and biogeochemical cycling within the CZ; Intersections of society and the CZ; Policy or management implications of CZ research; Development of CZ science networks; And case studies of successful national and international CZ collaborations.

Hydrological connectivity governs the transfer of water, sediment, solutes, and energy across forested catchments. It is strongly influenced not only by topography, vegetation cover, and climate, but also by managed infrastructure elements and proxies that create, enhance, or interrupt flow pathways. These include roads and skid trails, drainage ditches, culverts, embankments, drainage networks (including surface and subsurface systems like tile drains), reconnection measures, wetlands, beaver-related structures, and other land and water management interventions.
This session focuses on how such elements modify surface and subsurface connectivity, runoff generation, infiltration, groundwater–surface water exchange, erosion, nutrient and sediment delivery, flood wave propagation, and drought buffering in forested catchments. We particularly welcome studies that quantify connectivity through field observations, remote sensing, LiDAR, GIS, indices, modelling, or proxy-based approaches, and that translate these insights into management, planning, or decision-support frameworks.
We invite contributions across hillslope to catchment to regional scales, and across hydrology, geomorphology, ecohydrology, remote sensing, and landscape management. Of particular interest are studies that show how altering connectivity can reduce flood risk, enhance drought resilience, support sediment control, and improve catchment adaptation under climate extremes.

Land-use and land-cover changes can substantially modify hydrological processes, erosion and sediment dynamics in catchments. This session welcomes studies investigating the effects of past, ongoing and projected land-use and land-cover changes, including their interactions with climate change. Contributions may focus on hydrological or sediment-related processes, or their interactions, using different methodologies: distributed and semi-distributed models, remote sensing, machine learning, data-driven approaches or hybrid modelling frameworks. We particularly encourage studies that work on scenario analysis, model uncertainty, scale effects, process understanding and future projections.

River basins are increasingly affected by compound, sequential, and spatially clustered hydro-climatic extremes. At the same time, many basins have interconnected reservoirs, diversions, and regulated river reaches. These systems can change how extreme events move through a catchment. Reservoir storage and operational decisions can amplify, reduce, delay, or transfer these effects. Therefore, studying individual reservoirs or isolated extreme events may not fully capture the response of the entire basin.
This session aims to advance understanding of cascading hydrological extremes and basin-scale responses in regulated river systems. We welcome observational, theoretical, statistical, and modelling studies addressing the interactions between hydro-climatic extremes, catchment processes, reservoir storage and releases, and downstream hydrological responses.
Topics of interest include: compound and sequential floods and droughts; dependence structures and spatial propagation of hydrological extremes; hydrological connectivity in regulated basins; multi-reservoir and basin-scale hydrological modelling; reservoir storage, yield and reliability under climate variability and change; forecast-informed and adaptive reservoir operation; real-time hydrological forecasting and flood routing; and interactions between extreme precipitation, snowmelt, glacier melt, reservoir inflows, and downstream discharge.
We welcome contributions using remote sensing and Earth observation, hydroinformatics, telemetry, data assimilation, machine learning, and hybrid physics–data-driven approaches to improve monitoring, prediction, and understanding of cascading hydrological responses. Studies from a wide range of hydro-climatic and physiographic settings, including mountain, snow- and glacier-fed, monsoon, temperate, tropical, arid and semi-arid basins are encouraged, as are comparative studies across different hydro-climatic settings and regulated and unregulated river systems.
The session seeks to bring together researchers working across hydrological observations, process-based and statistical modelling, forecasting, Earth observation, and water-resources management to identify common mechanisms controlling cascading hydrological responses and to develop improved approaches for understanding and managing extremes in regulated river basins.

Hydrological information is more available than ever, but substantial knowledge gaps remain which limit our ability to coherently explain and connect hydrological phenomena across spatial and temporal scales. Hydrological synthesis represents efforts to combine components or elements of existing knowledge to form a connected whole. These connections may be across geographic locations and scales, or across temporal windows and scales. This session will focus on the investigation of similarities and patterns among catchment hydrological responses and processes.
We welcome contributions that, e.g., focus on:
- Synthesis across places: using field observations across multiple sites or large sample hydrology datasets, to synthesize process-based explanations of hydrological phenomena
- Synthesis across timescales: connections between characteristic timescales of catchments, e.g., residence time and catchment response time
- Synthesis across processes: theoretical explanations of hydrological phenomena across multiple places or scales, e.g., what is the link of event recession timescales to seasonal streamflow patterns?
- Synthesis across signatures: connections among hydrological signatures at different time scales, e.g. connection of the streamflow seasonality to the long term mean flow
- Synthesis across models: new approaches to use modelling tools to make process and pattern interpretations
- Synthesis across data: new methods to identify hydrological patterns in data

Hydrologic data have traditionally been sparse in space and time, requiring process-based models to interpolate observations and predict fluxes under limited data availability. Rapid advances in observation technologies are now enabling near–real-time monitoring of complex hydrologic processes across a wide range of spatial and temporal scales, fundamentally transforming hydrology from data scarcity to data abundance. Fully exploiting these emerging observation systems requires parallel advances in digital tools for data processing, integration, modeling, and visualization. New digital solutions—including digital twins, real-time data platforms, and interactive visualization environments—play a critical role in translating novel observations and scientific insights into actionable information for water resources research, multi-sector management, and decision-making. Under accelerating environmental change, two-way data exchange between models, observations, and stakeholders is increasingly essential for responsive forecasting and intervention. This session invites contributions on next-generation hydrologic observation systems and multi-scale digital solutions that advance process understanding, modeling, and application. Topics of interest include, but are not limited to:
- Novel observation techniques enabling improved parametrization of hydrologic processes
- Integration and fusion of next-generation hydrologic observations into modeling frameworks
- Digital twins and other advanced digital representations of hydrologic systems
- Real-time forecasting, early-warning, and decision-support systems for water resources and hydrologic hazards
- Case studies demonstrating the operational use and societal impact of hydrologic digititalization
Hosted by the Digital Water Flagship (https://digitalwaters.fi)

Understanding and representing hydrological processes is the basis for developing and improving hydrological and Earth system models. Hydrological observations, experiments, Earth observations, and new data products are becoming increasingly available across spatial and temporal scales, opening new opportunities to improve the representation, parametrization, evaluation, and understanding of hydrological processes in models.
In this session, we welcome contributions that advance hydrological modelling through new approaches to process representation, model development, parametrization, and evaluation across spatio-temporal scales. We particularly encourage contributions that use new observations, experiments, or modelling concepts to improve our understanding and representation of hydrological processes, and that provide insights or approaches that can be transferred beyond individual study sites or applications.
Potential contributions could (but are not limited to):
1. Advance seamless modelling of spatial patterns in hydrology and land models using new data products and Earth observations, particularly where these data provide new constraints on process representation;
2. Improve model structure by representing often neglected or insufficiently represented processes in hydrological models, such as human impacts, river regulation, irrigation, and vegetation dynamics;
3. Provide novel concepts for improving the characterization of internal and external model fluxes and their spatio-temporal dynamics, including approaches that enable better representation and understanding of hydrological processes across scales;
4. Introduce new approaches for model calibration and evaluation, especially approaches that diagnose deficiencies in process representation, improve understanding of model behaviour, and/or improve model predictions under changing conditions;
5. Upscale experimental and process-based knowledge from plot, hillslope, or other small scales to catchment, regional, or larger-scale models;
We particularly encourage contributions that go beyond the application of established models to individual study sites and instead provide new insights, methods, or frameworks for improving process representation. Contributions demonstrating how observations, experiments, or novel modelling approaches can lead to improved and transferable process understanding and model representation are especially welcome.

Stable and radioactive isotopes and other natural and artificial tracers are useful tools to (i) fingerprint the sources of water and solutes in catchments, (ii) trace flow pathways, and/or (iii) quantify exchanges of water, solutes and particulates between hydrological compartments both in the natural and simulated environments. We invite contributions that demonstrate novel applications and recent developments of isotope and other tracer techniques in hydrological field studies and data driven or physical modelling in the areas of surface water-groundwater interactions, unsaturated and saturated zone, rainfall-runoff processes, cold-region hydrology, nutrient or contaminant transport, ecohydrology or other catchment processes.

A multitude of processes contribute to the hydrologic functioning of catchments. Traditionally, catchment hydrology has been centered around surface runoff, which is readily observable. But at the same time, invisible below ground processes entailing the storage dynamics and flows of water are still underexplored. This includes subsurface runoff, as well as feedbacks of subsurface processes to the surface and the specific role of soil moisture in shaping these fluxes. This session aims to bring together contributions on the following topics and to address gaps in observations, models, and understanding of hydrologic systems:
- Identifying, tracing, and modeling subsurface runoff generation at the catchment scale.
- Factors and mechanisms controlling subsurface water storage and fluxes
- How soil moisture measurements at different scales can be used to improve process understanding, models, and hydrologic theory
- Interactions of surface and subsurface hydrologic processes

All hydrology is local, and no catchment behavior is average. Yet as a community we often gravitate toward generalization — universal frameworks, transferable methods, and broad conclusions — sometimes at the cost of engaging seriously with what makes catchment response genuinely unique. This session therefore invites contributions that place the modelling case study and its uniqueness at the center. What is hydrologically special about your study site? What made modelling it challenging? Which solutions did you find? And what does that tell us about the limits of the one-size-fits-all thinking?
By bringing together a diverse collection of modelling case studies, this session celebrates hydrological diversity and argues that careful examination of the specific is one of the most powerful ways to advance our general understanding of hydrology.

Land use and climate change as well as legal requirements (e.g. the EU Water Framework Directive) pose challenges for the assessment and sustainable management of surface water quality at the catchment scale. Sources and pathways of nutrients and other pollutants as well as nutrient interactions need to be characterized to understand and manage the impacts in river systems. Additionally, water quality assessment needs to cover the chemical and ecological status to link the hydrological view with aquatic ecology.
Models can help to optimize monitoring schemes and provide assessments of future changes and management options. However, insufficient temporal and/or spatial resolution, a short duration of observations and the widespread use of different analytical methods limit the potential for model application. Moreover, model-based water quality calculations are affected by errors in input data, model errors, inappropriate model complexity and insufficient process knowledge or implementation. In addition, models should be capable of representing changing land use and climate conditions to meet the needs of decision makers under uncertain future conditions. Given these challenges, there remains a strong need for advances in water quality modeling.

This session aims to bring together scientists working on both experimental and modelling studies to improve the prediction and management of water quality constituents (e.g. nutrients, organic matter, algae, sediment) at the catchment scale. Contributions addressing the following topics are welcome:

- Experimental and modelling studies on the identification of sources, hot spots, pathways and interactions of nutrients and other, related pollutants at the catchment scale
- New approaches to develop effective water quality monitoring schemes
- Innovative monitoring strategies that support both process investigation and improved model performance
- Advanced modelling tools for integrating catchments and/or simulating in-stream processes
- Observational and modelling studies at the catchment scale that relate and quantify water quality changes to changes in land use and climate
- Measurements and modelling of abiotic and biotic interaction and feedback involved in the transport and fate of nutrients and other pollutants at the catchment scale
- Catchment management: pollution reduction measures, stakeholder involvement, scenario analysis for catchment management

The growing availability of large-sample and large-scale water quality datasets creates new opportunities to understand how water quality varies in space and time across diverse natural and human-influenced settings. Although homogenizing heterogeneous data remains challenging, such datasets move research beyond site-specific studies towards comparative, multi-catchment analyses that reveal emergent patterns in water quality responses. They also help identify the drivers of these patterns, including climate, geology, soil, land use and human activities, together with their interactions and evolution over time. Large-sample analyses support robust statistical and machine learning models and improve the transferability of findings across sites, ecosystem types and regions, thereby deepening our understanding of water quality controls and informing management under changing environmental conditions.
We invite contributions from scientists compiling and exploring large water quality datasets to unravel the natural and anthropogenic drivers shaping water quality patterns. Studies on any solute, such as major ions, nutrients, carbon, metals, emerging contaminants and other pollutants, in inland water ecosystems (streams, rivers, lakes, groundwater) and soils are welcome. Early career scientists are especially welcome. Topics include, but are not limited to:
1. Development and improvement of large water quality datasets
•Dataset compilation and harmonization across regions; data platform development
•QA/QC, treatment of data gaps, censored values and uncertainty
•Integration of high-frequency sensor, remote sensing and citizen science data
2. Innovative approaches to handling big datasets
•Machine learning and deep learning methods, explainable AI methods
•Process-based modelling and statistical approaches beyond machine learning
•Empirical and mechanistic analyses of concentration-discharge (C-Q) relationships
3. Spatial patterns, temporal trends and controls
•Regional contrasts and multi-scale trend analysis
•Driver-response relationships, including lagged responses to changing management and pressures
•Influence of hydrological regimes, climate variability, land cover, soil and geology, and human activity
4. Hot spots and hot moments
•Event-based or threshold-triggered changes during extremes (floods, droughts, heatwaves)
•Spatial clustering of high-impact areas and sources
•Seasonal timing of pollutant loading and retention

Quantifying and understanding how global change, such as climate change and extremes, land use change and socio-economic developments affects clean water availability across space and time is essential. This knowledge is key to ensuring sufficient water of suitable quality to meet both human and ecosystem needs at present day and in the future. Recent work has highlighted the importance of considering water quality as a key factor in limiting water supply for sectoral uses. Hence, there is an urgent need for tools such as models that span a gradient from purely statistical (e.g., machine learning) to process-based approaches, anticipating the combined impacts of climate and socio-economic changes on water quality and addressing the resulting environmental and societal consequences. Some of these tools, within both Bayesian and frequentist paradigms, enable consideration of prediction reliability, relating uncertainties to a decision makers’ attitudes and preferences towards risks, all while accounting for the uncertainty related to our system understanding, data and random processes. We seek contributions that apply modeling and data-analytic approaches to:
• investigate the combined impacts on water quality and quantity from climate change and/or extremes across local to global scales, including climate impact attribution studies;
• investigate the impacts of present and future socio-economic developments on surface and/or groundwater quality;
• investigate the implications of compound and cascading extreme climate events (e.g., wildfire and floods, drought and heatwaves) on water quality;
• analysis of drivers and impacts of water quality, including agricultural and other diffuse sources, point-source inputs, and water quality effects on aquatic ecosystems and human health;
• quantify and couple supply and demand in support of water quality management including vulnerability assessment, scenario analysis, indicators, and the water footprint;
• project future water scarcity (combining water quality & quantity) supply and demand in the context of a changing climate;
• interpret and characterize uncertainties in machine-learning, AI and data-mining approaches that are trained on large data sets;
• address the problem of temporal and spatial scaling in water quality modelling;
• test transferability and generalizability of water quality predictions;
• application of remote sensing and/or citizen science in water quality estimates at multiple scales.

Our understanding of water pollution sources and their ecological impact has significantly advanced in the last decades. Major advancements have been possible thanks to automated water quality sensing techniques, novel separation techniques such as field-flow-fractionation, inferring ecological function from stream metabolism metrics and eDNA, and developments in modelling tools driven e.g. by the increasing access to high-resolution DEM data and satellite imaging. Further advancements are likely to emerge from the fusion of these datasets and techniques. This session will bring together examples of application of these novel tools for improving scientific understanding of dynamic freshwater ecosystems and their catchments, specifically for detecting water quality and stream ecology change over time and in response to natural and anthropogenic drivers such as global change. We also welcome contributions presenting examples of knowledge transfer to freshwater monitoring and management and freshwater-oriented collaborations between scientists, stakeholders, citizens, and authorities.

A large number of micropollutants, also known as trace contaminants or emerging contaminants, and their transformation products (veterinary and human pharmaceuticals, pesticides and biocides, personal care products, organic pollutants such as PFAS or chlorinated compounds) and heavy metals pose a risk for soil, groundwater and surface water. The large diversity of compounds and of their sources makes the quantification of their occurrence in the terrestrial and aquatic environment across space and time a challenging task. Regulatory monitoring programs cover a small selection out of the compound diversity and quantify these selected compounds only at coarse temporal and spatial resolution. Carefully designed monitoring, however, allows to detect and elucidate processes and to estimate parameters in the aquatic environment. Modelling is a complementary tool to generalize measured data and extrapolate in time and space, which is needed as a basis for scenario analysis and decision making. Mitigation measures can help reduce contamination of groundwater and surface water and impacts on water quality and aquatic ecosystems.
This session invites contributions that improve our quantitative understanding of the sources and pathways, mass fluxes, the fate and transport and the mitigation of micropollutants in the soil-groundwater-river continuum of catchments.

Topics cover:
- Novel sampling and monitoring concepts and devices
- New analytical methods such as new detection methods for micropollutants, non-target screening
- Experimental studies to improve process understanding and to quantify diffuse and point source inputs
- Biogeochemical interactions and impact on micropollutant behaviour
- Fate studies on parent compounds and transformation products
- Modelling approaches (including hydrology and sediment transport) to simulate pollutant transport and fate at several spatial and temporal scales
- Spatial and temporal monitoring to elucidate transport processes and to support modelling
- Modelling tools for decision support
- Setup of mitigation measures and evaluating their effectiveness.
- Methods to evaluate water quality modelling uncertainty, and/or combining data and modeling (data assimilation)

Micro- and nanoplastics (MNPs) are increasingly detected in soils, groundwater, rivers, lakes, wetlands, and sediments. Despite growing evidence of their widespread occurrence, the mechanisms controlling their mobilisation, transport, retention, transformation, and transfer between environmental compartments remain poorly constrained. MNP behaviour is influenced by particle properties and by the hydrological, physical, and biogeochemical characteristics of the surrounding environment. Processes such as runoff, infiltration, recharge, erosion, sediment transport, and groundwater–surface water exchange can govern their movement, while interactions with soil and sediment matrices, organic matter, minerals, microorganisms, and biofilms may promote retention, remobilisation, aggregation, or transformation. MNPs may also interact with co-occurring pollutants, including metals, pesticides, pharmaceuticals, PFAS, nutrients, and other emerging contaminants. These interactions can influence contaminant mobility, persistence, bioavailability, and exposure, raising important questions about the role of plastic particles within complex contaminant mixtures and their implications for ecosystem health.
We invite contributions examining MNP occurrence, transport and retention mechanisms, surface–subsurface connectivity, transformation and remobilisation, interactions and co-transport with other contaminants, biological interactions, exposure, and environmental risk. Field investigations, laboratory experiments, analytical advances, monitoring approaches, numerical and process-based modelling, and risk assessments are particularly encouraged. The session aims to connect researchers across hydrology, hydrogeology, soil and freshwater sciences, environmental chemistry, engineering, and ecotoxicology to advance a process-based understanding of MNP fate and risks across interconnected environmental systems.

Plastic pollution in freshwater systems is a widely recognized global problem with potential environmental risks to water quality, biota and livelihoods. Furthermore, freshwater plastic pollution is also considered the dominant source of plastic input to the oceans. Despite this, research on plastic pollution has only recently expanded from the marine environment to freshwater systems. Therefore data and knowledge from field studies are still limited in regard to freshwater environments. Sources, quantities, distribution across environmental matrices and ecosystem compartments, and transport mechanisms remain mostly unknown at catchment scale. These knowledge gaps must be addressed to understand the dispersal and eventual fate of plastics in the environment, enabling a better assessment of potential risks as well as development of effective mitigation measures.

This session welcomes contributions from field, laboratory and modelling studies that aim to advance our understanding of river network and catchment-scale plastic transport and accumulation processes. We are soliciting studies dedicated to all plastic sizes (macro, micro, nano) and across all geographic settings. We are especially encouraging studies that can link plastic accumulation and transport to catchment-wide hydrological, ecological or geomorphological processes that we can better understand where, when and why plastics accumulation takes place in aquatic-terrestrial environments.
In this session, we explore the current state of knowledge and activities on macro-, micro- and nanoplastics in freshwater systems, focusing on aspects such as:
• Transport processes of plastics at catchment scale;
• Source to sink investigations, considering quantities and distribution across environmental matrices (water and sediment) and compartments (water surface layer, water column, ice, riverbed, and riverbanks);
• Plastic in rivers, lakes, urban water systems, floodplains, estuaries, freshwater biota;
• Effects of hydrological extremes, e.g. accumulation of plastics during droughts, and short-term export during floods in the catchment;
• Modelling approaches for global river output estimations;
• Legislative/regulatory efforts, such as monitoring programs and measures against plastic pollution in freshwater systems.

Water temperature is crucial for ecosystems and society, and is strongly driven by climate, environmental and human factors. Extreme water temperature and variability can severely impact these systems by altering physical processes (e.g. lake evaporation and stratification), biological functioning (e.g. deoxygenation and fish mortality) or limiting the usefulness to humans (e.g. drinking water quality, cooling water use and power generation potentials). Water temperature is also used as a tracer for hydrological processes, enabling us to understand interactions of different hydrological components such as groundwater recharge, runoff processes and lake in- and outflow.

This session aims to bring together freshwater temperature researchers from both the surface (i.e. springs, rivers, streams, lakes and reservoirs) and subsurface waters (i.e. soil and groundwater) communities, to shed light on the natural and anthropogenic processes governing freshwater temperature, and the resulting implications for ecosystem health, water resources management and sectoral uses. We are interested in spatio-temporal patterns and historic or future trends of water temperature and its extremes, their impact on aquatic biogeochemistry and ecosystems, as well as different types of water temperature modelling approaches (e.g. process-based, machine learning).

We welcome submissions that investigate water temperature dynamics across various temporal and spatial scales (local to global) in any inland water bodies using field and lab experiments, large-scale and -sample analyses, and modelling approaches.

This session advances modern water quality science by multi-platform observation, process-level understanding and intelligent governance. It highlights climate and human impact analysis, hybrid process–machine learning modelling, updated assessment standards, and smart digital management. We welcome cross-disciplinary work linking observation, simulation and governance, including transboundary water quality cooperation, to build more resilient, adaptive solutions for global water quality challenges.
This session invites cutting-edge abstracts spanning the following priority research areas (topics are not restricted to the listed items):
 Space–air–ground integrated monitoring systems for water quality assessment;
 Novel monitoring technologies for the detection of pathogens and (micro)biological parameters;
 Transport and transformation processes of nutrients, contaminants, and emerging pollutants
 Impacts of ecological processes, climate change and human activities on water quality

Session Description

The Anthropocene is characterized by unprecedented human pressures on aquatic environments, with rapid urbanization, industrialization, intensive agriculture, mining, and climate change increasingly affecting the quality and availability of water resources. Emerging and persistent contaminants—including pharmaceuticals, pesticides, heavy metals, nutrients, microplastics, pathogens, and other chemical pollutants—pose complex challenges to freshwater and coastal ecosystems and may create significant risks to human and environmental health. Understanding the sources, transport, transformation, fate, and impacts of these contaminants is therefore essential for safeguarding water security and ecosystem integrity.

This session, “Safeguarding Water Quality in the Anthropocene: Contaminants, Health and Sustainable Management,” will bring together interdisciplinary research addressing contemporary and emerging challenges in water quality. Contributions are invited on contaminant monitoring and assessment, advanced analytical and sensing technologies, pollutant fate and transport, exposure pathways, ecological and human health impacts, risk assessment, and innovative approaches for water and wastewater treatment. The session will also explore nature-based solutions, circular approaches, remediation strategies, and data-driven and integrated frameworks for sustainable water-quality management.

By connecting environmental science, hydrology, engineering, public health, ecology, and policy, the session aims to foster knowledge exchange and identify science-based pathways for protecting water resources and supporting resilient, healthy, and sustainable aquatic systems in the Anthropocene.

Floods and droughts have major impacts on society and ecosystems and are projected to become more frequent and severe with climate change. This session seeks to unite the flood and drought research communities by studying the similarities in their processes and study approaches to identify synergies. We aim to deepen understanding of the processes governing these hydrological extremes and their interplay, develop robust methods for data analysis and modeling of floods and droughts and their transitions, assess the influence of global change on hydro-climatic extremes, and study the socio-economic and environmental impacts of both types of extremes. We seek studies where:
- (new) methods advance process understanding
- the inclusion of that understanding advances indicators, analysis, and modeling.
- methods are demonstrated to be fit for purpose, transparant, and robust.
We welcome submissions that present insightful flood and/or drought research, including case studies, large-sample studies, statistical hydrology, and analyses of flood or drought non-stationarity under the effects of climate-, land cover-, and other anthropogenic changes. Studies that investigate both extremes, or their interplay, are of particular interest.

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

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

Large-sample hydrology (LSH) is essential for understanding and predicting hydrological variability and change across spatiotemporal scales. The field has advanced significantly in recent decades, supported by the growing availability of datasets including a large variety of hydrological systems. The session highlights recent advances in LSH, with a focus on understanding hydrological variability by making use of large-sample datasets, developing and improving these datasets, and working towards catchment classification and characterization. We welcome abstracts that contribute to these topics, particularly (but not exclusively) related to the following sub-topics:
1. Enhance process understanding based on LSH:
How can we use large-sample datasets to improve and synthesize hydrological process understanding and to transfer knowledge obtained in well-monitored catchments to data scarce regions? How can we bridge and consolidate findings from large-sample analyses with our understanding of hydrological processes from well-monitored or experimental catchments?
2. Develop and improve large-sample datasets:
How can we address current challenges, e.g., uneven spatial coverage, representativeness of catchment descriptors, dataset harmonization, and uncertainty quantification? How can we expand large-sample datasets by, e.g., including data at higher spatial and temporal resolution or real-time data? How can we ensure data quality? What new, unconventional data sources might be exploited? How can we (systematically) represent anthropogenic influences in large-sample datasets?
3. Advance hydrologic modeling:
How can we improve process-based and data-driven modeling by using LSH? How can functional knowledge obtained from large-sample studies be transferred to ungauged basins or data-scarce regions through modeling? How can we develop new models and workflows to evaluate hydrological response under change, also with regard to human impacts? How can processes that extend beyond the topographic catchment boundaries, e.g., groundwater or water quality, be integrated into large-sample hydrological models?
4. Improve catchment classification and characterization:
How can we use static and dynamic catchment descriptors available in large sample datasets to derive groups of catchments with similar hydrologic behavior? How can we improve catchment characterization, e.g., by developing and including new descriptors or replacing static with dynamic attributes?

Research on changes in the pace of the water cycle dates back to the 1970s. In the last few decades, leveraging a number of new regional and global datasets, research has highlighted changes in the water cycle and distribution attributed to secular trends in relevant processes and/or to anthropogenic activities, such as irrigation, groundwater pumping, dam and reservoir operations. For example, studies have investigated changes in the rate of exchange across terrestrial water storages and land-atmosphere interactions using different datasets, including remotely sensed, modeled, or data-assimilated, and reanalysis products. Past studies have also differed in their period of analysis, regional focus, and methods for change detection, attribution, and uncertainty assessment. This session aims to provide a platform to present and discuss studies that seek to understand:

(i) The current state of knowledge regarding the role of climatic change and human water management in influencing land-atmosphere interactions.
(ii) How these factors result in accelerating or decelerating water cycle processes, with implications for droughts, floods, and other hydroclimatic extremes.
(iii) Attribution of changes in water fluxes, storages, and land-atmosphere interactions to climate variability, long-term climate change, and human water and land management.
(iv) Uncertainties and open questions related to this critically important research topic.

Studies focused on change analysis of individual or integrated water cycle components and land atmosphere interactions using one or more of the above-mentioned data types and conceptual, coupled, or impact modeling techniques are encouraged, with either a regional or global focus. Contributions utilizing emerging observational capabilities, including gravity-based observations, surface water monitoring, and flux measurements, are particularly welcome. We also encourage studies that quantify and attribute changes in water fluxes, storages, and land-atmosphere interactions, highlight associated uncertainties, and disentangle the relative roles of climate variability, long-term climate change, and human water and land management. This especially includes interdisciplinary studies that improve our understanding of Earth system feedbacks and inform sustainable water management under global change.

The space-time dynamics of floods are controlled by atmospheric, catchment, riverine and anthropogenic processes, and their interactions. The natural oscillation between flood-rich and flood-poor periods is superimposed on anthropogenic climate change and human interventions in rivers and catchments, such as the construction of reservoirs, alterations in river morphology, water retention capacity and land use. In addition, flood risk is further shaped by continuous changes in exposure and vulnerability. In this complex setting, it remains unclear what is the relative contribution of each factor to the space-time dynamics of flood risk. The scope of this session is to report when, where, how (detection) and why (attribution) changes in the space-time dynamics of floods occur. The session particularly welcomes presentations on attributing different drivers to observed changes in flood risk. Presentations on the impact of climate variability and change, land use transitions, morphologic changes in streams, and the role of pre-flood catchment conditions in shaping flood risk are also welcome. Furthermore, contributions on the impact of socio-economic factors, including adaptation and mitigation of past and future risk changes are invited. The session will further stimulate scientific discussion on the detection and attribution of flood risk change. Specifically, the following topics are of interest for this session:

- Long-term changes in rainfall patterns and flood occurrence;
- Process-informed extreme value statistics;
- Interactions between rainfall distribution and catchment conditions in shaping flood patterns;
- Detection and attribution of flood hazard changes, such as atmospheric drivers, land use controls, natural water retention measures, reservoir construction, and river training;
- Changes in flood exposure: economic and demographic growth, urbanisation of flood prone areas, implementation of multi-scale risk mitigation measures (particularly structural defences);
- Changes in flood vulnerability: changes of economic, societal and technological aspects driving flood vulnerability and private precautionary measures;
- Multi-factor decomposition of observed flood damages combining the hydrological and socio-economic drivers;
- Future flood risk scenarios and the role of adaptation and mitigation strategies.

Global warming has fundamentally altered the statistical behavior of the Earth’s climate system, introducing non-stationarity across the atmosphere, oceans, and land. Variations in atmospheric circulation, such as shifts in monsoon systems, jet streams, and subtropical highs, have induced changes in oceanic dynamics, including sea surface temperature anomalies, altered circulation patterns, and marine heatwaves. These coupled atmospheric-oceanic processes, in turn, drive evolving hydroclimatic patterns on land, directly influencing precipitation regimes, streamflow variability, and the frequency and intensity of extreme events like floods, droughts, and compound extremes. This session aims to foster interdisciplinary discussion on detecting, modeling, and understanding non-stationarity across the interconnected Earth system. We invite contributions that assess or model non-stationarity in atmospheric, oceanic, or hydrological domains, along with its cascading impacts on hydroclimatic variability. We highly encourage research addressing individual and compound extremes, large-scale teleconnections, or regional climate responses. We also welcome submissions employing observational data analysis, climate and hydrological modeling, statistical and dynamical frameworks, and machine learning to explore how non-stationarity propagates across Earth system components. By integrating diverse perspectives from hydrology, atmospheric sciences, oceanography, and the broader geosciences, this session seeks to advance our understanding of evolving hydroclimatic extremes and support improved prediction, adaptation, and resilience strategies under a changing climate.

In the current context of global change, a better understanding of our large-scale hydrology is vital. For example, by increasing our knowledge of the climate system and water cycle, improve assessments of water resources in a changing environment, perform seasonal predictions, and evaluate the impact of transboundary water resource management.

We invite contributions from across hydrological, atmospheric, and earth surface processes communities. In particular, we welcome abstracts that address advances in:
(i) understanding and predicting the present and future state of water resources worldwide and within large-scale systems, including hydrological extremes and uncertainty assessment.
(ii) the use of global Earth observations and in-situ datasets for large-scale hydrology and data assimilation techniques for large-scale hydrological models, including machine learning and hybrid modelling approaches.
(iii) the representation and evaluation of various components of the terrestrial water cycle fluxes and storages (e.g., soil moisture, snow, groundwater, lakes, floodplains, evaporation, river discharge) and atmospheric modelling.
(iv) providing syntheses that combine knowledge gained at smaller scales (e.g. catchments or hillslope) to increase our knowledge on process understanding needed for further development of large-scale hydrological models and to identify large-scale patterns and trends.
(v) understanding interactions and feedbacks between hydrological processes, water management, and human intervention activities (e.g. reservoirs, dams, irrigation) across large-scale systems.

Different approaches, including global models, data-driven approaches, and machine learning, are used to assess water balance components at the global, continental, and regional scales. By making use of in-situ as well as remotely sensed observations, they attempt to quantify water fluxes (e.g., evapotranspiration, streamflow, groundwater recharge) and water storage on the terrestrial part of the Earth as a whole (e.g., from GRACE/-FO and future missions such as MAGIC and NGGM) or in separate compartments (e.g., water bodies, snow, soil, groundwater). Increasing attention is given to uncertainties that stem from forcing datasets, model structure, parameters and combinations of these. Recent advances also include hybrid approaches that integrate machine learning with process-based models and assimilate Earth Observation data for improved water balance closure. Current research shows that flux and storage estimates differ considerably due to the methodology and datasets used, so a robust assessment of global, continental and regional water balance components remains challenging.

This session is seeking contributions, including:

1) past/future assessment of water balance components (fluxes and storages) such as precipitation, freshwater fluxes to the oceans (or inland sinks), evapotranspiration, groundwater recharge, water use, changes in terrestrial water storage or individual components at global, continental and regional scales,

2) application of innovative explorative approaches undertaking such assessments – through better use of advanced data-driven and statistical approaches, mechanistic models, machine learning and approaches to assimilate (or accommodate) in-situ and remote sensing datasets for improved estimation of terrestrial water storages/fluxes,

3) analysis and quantification of different sources of uncertainties in estimation of water balance components,

4) examination and attribution of systematic differences in storage/flux estimates between different methodologies, and/or

5) applications/consequences of those findings, such as sea level rise and water surplus or scarcity.

We encourage submissions based on different methodological approaches that estimate and analyse water balance components individually or integratively on global, continental, or regional scales. Assessments of uncertainty in past/future estimates of water balance components and their implications are highly welcome.

Hydrological systems are undergoing profound changes in response to climate variability, to rising greenhouse gas concentrations, and to direct human interventions. Over recent decades, shifts in precipitation, evapotranspiration, streamflow, and water storage have been accompanied by increasing frequency and intensity of hydrological extremes. How these changes and their interactions will impact the terrestrial water cycle and other Earth system dynamics remains poorly understood and is the origin of much uncertainty, which limits our ability to build societal and ecosystem resilience – contributing to policy challenges for adaptation to water scarcity and other hydro-climatic risks.
At the same time, the research community now has unprecedented opportunities. Expanding in-situ networks, advances in remote sensing, and more complex and higher resolution Earth system and land surface models provide powerful tools to explore hydrological processes across scales. Yet, significant uncertainties remain and there have been concerns that advances in modelling and observational systems are not accompanied by advances in theory. Observational studies and global model simulations often yield divergent conclusions, revealing persistent knowledge gaps in how climate change, rising atmospheric CO2, and anthropogenic activities interact to reshape hydrological systems.
We invite submissions that address, but are not limited to, the following themes where we would like to hear about recent advances as well as current knowledge gaps:
1. Advanced ground- and space-based techniques and data-model fusion approaches for estimating hydrological variables (precipitation, evapotranspiration, streamflow, and water storage) and extremes (floods and droughts) from catchment to global scales.
2. Responses and feedbacks of hydrological processes and extremes to climate change and human activities.
3. Impacts of land use, land cover change, irrigation, and water withdrawals on streamflow regimes and hydrological extremes.
4. Projections of regional and global hydrological changes and extremes under near- and long-term climate scenarios.
5. Benchmarking hydrological and Earth system models against current observations, with particular attention to CO2 effects and human water use.
6. Hydrological processes and extremes in hotspot regions such as the Tibetan Plateau, the Arctic, the Amazon, and intensively irrigated areas.

The South American hydroclimate encompasses a wide range of regimes shaped by complex interactions among the Amazon, the Andes Cordillera, and large-scale atmospheric circulation and oceanic variability. This diversity presents unique opportunities to advance hydrometeorological science, while posing significant challenges for understanding, monitoring, predicting, and managing water resources in a changing climate. Advances in Earth observation, remote sensing, artificial intelligence, and numerical modeling are improving our ability to observe, model, and forecast these processes across spatiotemporal scales. This session brings together researchers and practitioners across climatology, meteorology, hydrology, hydroclimatology, water resources, environmental risks, and climate services to showcase recent research advances, experiences, challenges, and opportunities in South America. We invite contributions in four areas: (1) Process understanding: hydroclimatic processes, conceptual and physically based modeling, AI-driven approaches and hypothesis testing locally and across large scales as well as under past and future climate conditions; (2) Monitoring: in situ observations, remote sensing, and low-cost innovative monitoring systems; observational datasets at a regional scale (3) Prediction and assessment: forecasting across timescales, hydroclimatic extremes, downscaling approaches, trend analyses, climate change impact assessments, and compound and multi-hazard risks; and (4) Management and solutions: water resources management, climate services, decision-support tools, and climate adaptation strategies. By fostering regional and international collaboration, this session provides a dedicated space to exchange experiences, compare approaches across diverse hydroclimatic regimes, and advance hydrometeorological science, ultimately strengthening resilience to hydroclimatic variability and change across South America.

Water moves continuously between the atmosphere, the land surface and the subsurface, yet models are usually built for one compartment at a time. Atmospheric models simplify land and groundwater processes, hydrological models treat precipitation as fixed input, and groundwater models often reduce recharge to a boundary condition. Human interventions such as reservoirs, irrigation, pumping, land-use change and grey–green infrastructure further alter these connections. The gaps matter most during extremes: floods, droughts, landslides, subsidence and seawater intrusion often arise from processes that cascade across compartments, and models that miss these links can underestimate hazard and misjudge risk.

This session welcomes process-based, data-driven and hybrid modelling studies, from plot to global scale, on topics including: (1) atmospheric water, such as precipitation downscaling, extreme rainfall, land–atmosphere coupling and moisture recycling; (2) land-surface and subsurface water, such as runoff, soil moisture, evapotranspiration, snow and glacier melt, recharge, groundwater flow and surface water–groundwater exchange; (3) coupled frameworks linking compartments across scales; (4) human interventions and their feedbacks on the water cycle; (5) hydrological hazards and risk, including compound and cascading events, hazard, exposure and vulnerability assessment, and impact-based early warning; (6) machine learning, physics-informed and explainable AI, data assimilation and digital twins; and (7) uncertainty, scenario analysis and decision support.

We particularly welcome studies from data-scarce, Mediterranean and monsoon-dominated regions, work that tests models against observed events, approaches that link hazard modelling to risk reduction and water management, and model intercomparisons or benchmark datasets that help the community move forward. Early-career scientists are strongly encouraged to submit.

Heavy precipitation events in small and medium-sized catchments can cause flash floods with very short lag times (a few hours) and high specific peak discharges. The rainfall and resulting rapid runoff can initiate geomorphic processes such as erosion, debris flows or shallow landslides, which mobilize large amounts of unconsolidated material and increase their destructive force.
Robust hazard assessments combined with early warning systems are essential to reduce the impacts of these events by enabling effective emergency management. This can be achieved by (i) increasing the forecast skill (improved predictions of physical variables or the hazard), or (ii) integrating additional information to support decision making.
Uncertainty sources in the forecasting chain include the high space-time variability of rainfall, limitations in observations and forecasts, the variability and nonlinearity of physical processes and their representation in models under extreme conditions, and incomplete exposure and vulnerability data to translate hazard forecasts into impacts.
This session presents recent advances in the monitoring, modeling and short-range forecasting of rainfall-induced hazards, the identification of hazard-prone areas, and the assessment of societal impacts with contributions on these themes:

- Development of new measurement techniques adapted to flash floods and hydro-geomorphic hazards (in-situ sensors and remote sensing data), and quantification of associated uncertainties.
- Short-range rainfall forecasting for heavy precipitation events, including seamless rainfall forecasting based on NWP models, nowcasts and/or ML, and ensemble-based uncertainty representation.
- Understanding and modeling of flash floods, hydro-geomorphic processes and their cascading effects, at appropriate space-time scales.
- Integrated hydrometeorological forecasting chains and new modeling approaches for flash floods and geomorphic hazards in gauged and ungauged basins.
- Observation, understanding and prediction of hazard, societal vulnerability and social responses to flash floods and/or hydro-geomorphic hazards.
- Development of impact-based approaches, integrating societal vulnerability.
- New approaches to validate hydrometeorological and impact forecasts, including new direct and indirect observation techniques.
- Assessment of possible evolutions in frequency and hazard characteristics due to climate change.
Contributions related to recent events are encouraged.

Drought and water scarcity affect many regions of the Earth, including areas generally considered water rich. The projected increase in the severity and frequency of droughts may lead to an increase in water scarcity, particularly in regions that are already water-stressed, and where overexploitation of available water resources can exacerbate the consequences of drought. This may lead to long-term environmental and socio-economic impacts.

Drought monitoring, forecasting and early warning constitute one of the three pillars of integrated drought management. It is therefore necessary to improve monitoring and sub-seasonal to seasonal forecasting of drought and water availability, and to develop innovative indicators and methodologies that translate data into actionable information to support effective drought early warning and risk management.

This session addresses statistical, remote sensing, physically-based techniques, as well as artificial intelligence and machine learning techniques aimed at monitoring, modelling and forecasting hydro-meteorological variables relevant to drought and water scarcity. These include, but are not limited to, precipitation, extreme temperatures, snow cover, soil moisture, streamflow and groundwater levels, together with the interactions and propagation pathways linking different drought types across the hydrological cycle. The development and implementation of drought indicators meaningful to decision-making processes, and approaches for presenting and integrating these with the needs and knowledges of water managers, policymakers and other stakeholders, are also addressed in this session. Contributions focusing on the interrelationships and feedbacks between drought, low flows and water scarcity, and the impacts these have on socio-economic sectors including agriculture, energy and ecosystems, are welcomed.

The session aims to bring together scientists, practitioners and stakeholders in the fields of hydrology and meteorology, as well as water resources and drought risk management. Particularly welcome are applications and real-world case studies, both from regions that have long been exposed to significant water stress and from regions that are increasingly experiencing water shortages due to drought, where drought early warning, supported by state-of-the-art monitoring and forecasting of water availability, is likely to become more important in the future.

This interactive session aims to bridge the gap between research and practice in operational forecasting, with a focus on impact-based approaches for flood, water scarcity and multiple hazards.
Operational (early) warning systems are the result of progress and innovations in the science of forecasting. New opportunities have risen in physically based modelling, AI/machine learning, coupling meteorological and hydrological forecasts, ensemble forecasting, impact-based forecasting, and real-time control. Often, the sharing of knowledge and experience about developments are limited to the particular field (e.g. flood forecasting or landslide warnings) for which the operational system is used. Increasingly, humanitarian, disaster risk management and climate adaptation practitioners are using forecasts and warning information to enable anticipatory early action that saves lives and livelihoods. It is important to understand their needs, their decision-making process and facilitate their involvement in forecasting and warning design and implementation (co-generation).

The focus of this session will be on bringing the expertise from different fields together as well as exploring differences, similarities, problems and solutions between forecasting systems for varying hazards including climate emergency. Real-world case studies of system implementations - configured at local, regional, national, continental and global scales - will be presented. An operational warning system can include, for example, monitoring of data, analysing data, making and visualizing forecasts, impact-based solutions, giving warning signals and suggesting early action and response measures.

Contributions are welcome from both scientists and practitioners who are involved in developing and using operational forecasting and/or management systems for climate and water-related hazards, such as flood, drought, tsunami, landslide, hurricane, hydropower etc. We also welcome contributions from early career practitioners and scientists, and those working in multi-disciplinary projects (e.g., EU Horizon Disaster Resilience Societies).

Early warnings must be understandable, trusted and actionable to help protect lives and livelihoods from natural hazards such as floods, droughts, heatwaves, tropical cyclones, storms and tsunamis. Recent disasters, such as the 2021 floods in Western Europe, the 2020-2023 Horn of Africa drought, and the extreme heat affecting parts of Europe and the Mediterranean region in 2026 show that significant gaps in the early warning - early action chains persist. The Early Warnings for All initiative (led by WMO, UNDRR, ITU, and IFRC) recognizes that increased efforts are required to develop effective impact-based multi-hazard early warning systems.

The scientific community needs to move beyond natural hazard forecasting and towards impact- and action-based forecasting. This, in turn, requires commitment to the creation and dissemination of multi-hazard risk and multi-source impact data (including from social media) as well as the design, implementation and evaluation of impact-based forecasting services and linked early warning - early action (EW-EA) protocols.

However, significant knowledge gaps and operational challenges persist. This session aims to offer valuable insights and share best practices on impact-based early warning systems from the perspective of both the knowledge producers and users.

Topics of interest include, but are not limited to:
- Practical applications and operational use cases of impact-based forecasts, including the challenges faced in operational implementation
- Novel physics-based, Artificial Intelligence (AI) and hybrid approaches integrating forecasting, big data and earth observations for impact-based forecasting and decision support, including responsible, transparent and explainable approaches that support trusted, inclusive and people-centred systems
- Development of cost-efficient and evidence-based early action portfolios
- Linking preparedness and anticipatory action with response, recovery, reconstruction and prevention efforts
- Development of operational trigger systems (forecast-based financing) for humanitarian anticipatory action
- User-centred evaluation of impact-based forecasting and warning products including usability, trust, decision relevance and actionability
- Triangulation of indigenous and scientific knowledge for leveraging forecasts, multi-hazard risk information and climate services to last-mile communities
- Bridging the gaps in risk, impact and early action data to support impact-based forecasting.

Real-time flood forecasting and early warning are rapidly evolving through advances in Earth observation, sensor networks, data assimilation, artificial intelligence (AI), machine learning (ML), high-performance computing, and digital technologies. These developments offer new opportunities to improve forecast accuracy, lead time, spatial resolution, uncertainty estimation, and the translation of forecasts into actionable warnings.
This session invites contributions covering the full chain from real-time data to forecasting, impact assessment, warning, and early action. We particularly welcome studies combining process-based knowledge with emerging data-driven and hybrid approaches, as well as innovative operational applications.
Topics include, but are not limited to:
• Real-time data: ground observations, radar, satellite and remote sensing, IoT, crowdsourcing, data quality control, imputation, assimilation, and multi-source data fusion.
• Flood forecasting: process-based, conceptual, hybrid, AI/ML and physics-informed approaches; nowcasting; rapid forecasting; and forecasting in data-scarce regions.
• Uncertainty and reliability: ensemble and probabilistic forecasting, uncertainty quantification, explainable AI, model transferability, robustness, and extreme-event forecasting.
• Forecast-to-action: impact-based forecasting, inundation and damage prediction, early warning and anticipatory action, decision-support systems, and communication of forecast uncertainty.
• Digital innovations: digital twins, cloud and edge computing, high-performance computing, open-source platforms, and immersive visualisation.
• Operational and community applications: real-world forecasting systems, stakeholder engagement, citizen science, emergency response, and community-centred early warning.
• Emerging directions: foundation models, generative AI, multimodal data fusion, autonomous forecasting, and next-generation Earth-system and hydrological digital twins.

Flood forecasting and inundation modelling are critical components of disaster risk reduction, especially under the increasing pressures of climate variability, rapid urbanization, and land-use change. Recent advances in high-resolution satellite observations, ensemble Numerical Weather Prediction (NWP) products, expanding hydro meteorological networks, and high-performance hydrodynamic models—enabled by localized data, growing computing power, and fast surrogate emulators provide new opportunities to enhance predictive capability and reliability. This session seeks contributions that highlight methodological innovations and practical applications in flood forecasting and floodplain inundation modelling. The session welcomes studies that integrate diverse data sources, explore multi-scale modelling strategies, and advance process-based, statistical, and hybrid machine learning/AI frameworks. Emphasis is placed on the role of data assimilation in improving forecast accuracy, reducing uncertainty, and supporting real-time decision making. Case studies demonstrating the transition from research to operations, applications in reservoir management, adaptive pump and gate operations informed by distributed sensor networks, and emergency response efforts, as well as strategies to communicate probabilistic forecasts to end users, are of strong interest. We also invite discussions of uncertainty quantification and the challenges of applying models across diverse hydrological and climatic settings. The session aims to bring together hydrologists, meteorologists, remote sensing specialists, and data scientists to foster cross-disciplinary dialogue and promote innovative approaches that strengthen flood risk management worldwide.

Multi-hazard early warning systems increasingly rely on the technical core of modern disaster risk reduction. They utilise heterogeneous data streams, including earth observations, in-situ sensor networks, process-based models, AI and data-driven approaches, and increasingly citizen-reported and computer-vision-derived observations. These datasets need to be transformed into forecasts that are both scientifically robust and operationally actionable, ranging from minutes to hours for rapid-onset hazards, such as floods, landslides, and cyclones, to months and seasons for slow-onset hazards such as drought. Moreover, natural hazards increasingly occur concurrently, consecutively, or in combination, creating multi-hazards and cascading risks. Operational early warning systems, however, often focus on single hazards. In addition, warning thresholds and dissemination pathways frequently fail to translate warnings into effective community and institutional response, creating a persistent know-do gap that cannot be closed through additional sensing and technical sophistication alone.

This session welcomes contributions across the full arc of multi-hazard early warning, including: (i) AI/ML and process-based modelling approaches for multi-hazard forecasting and nowcasting (e.g., floods, droughts, landslides, and cascading hazards); (ii) data fusion architectures combining satellite EO, real-time sensor networks, and computer vision for hazard detection; (iii) participatory and citizen-science methodologies, local and traditional knowledge integration, and including living labs and serious games for co-creating warnings directly with at-risk communities; (iv) dashboard and decision-support system design that translate model outputs into actionable, trusted, inclusive, and often multilingual alerts for operational use; and (v) validation and lessons from deployed or piloted systems at the interface between technical performance and community uptake.

We particularly encourage submissions presenting multi-hazard forecasting approaches, warning thresholds, and deployed or piloted systems, including honest lessons on where technical sophistication and last-mile trust have, and have not, come together to support effective action.

In recent years, there has been a strong increase in the use of machine learning techniques to enhance hydrological simulation and forecasting. These methods are receiving growing attention due to their ability to handle large datasets, combine different sources of predictability, increase forecasting skill and minimize the effect of biases, as well as enhance computational efficiency. Furthermore, the range of implementations is broad, from purely data-driven forecasting systems to hybrid setups, combining both physically-based models and machine learning techniques, from large to local scales as well as different time horizons. These all allow forecasters to address and cover various aspects and processes of the hydrological cycle, including extreme conditions (floods and droughts), which are important for water resources and emergency management.

This session aims to highlight and bring together recent efforts in hydrological forecasting, using machine learning based techniques and/or hybrid approaches. Contributions are welcome showcasing examples of model developments (ranging from implementations to operational setups), studies ranging from local to global scales and across different time horizons (short-, medium- and long-term), as well as studies showcasing the efforts data-driven/hybrid approaches to tackle challenges in hydrological forecasting. We particularly welcome talks that reach beyond the description of machine learning architectures to uncover physical and human-induced processes, account for uncertainties, generate novel insights about hydrological forecasting, or support efforts in reducing common forecasting difficulties.

Other topics related to the subdivision of Hydrological Forecasting and the corresponding sessions can be found here: https://www.egu.eu/hs/about/subdivisions/hydrological-forecasting/

Anthropogenic activities have profoundly altered the hydrological cycle, particularly in heavily modified systems. Human interventions such as reservoirs, dams, drainage networks, urban expansion, infrastructure development, deforestation/afforestation, water abstraction, and wastewater discharge have reshaped natural processes and management practices. Under climate change, these alterations further shift the frequency, magnitude, and seasonality of hydroclimatic extremes, potentially amplifying risks for societies and ecosystems.

Despite advances in hydrological science and technology, our understanding of human–water interactions across scales remains limited. Challenges stem from the complexity and uncertainty in quantifying human influences, the scarcity of long-term records, and the limitations of conventional models often designed for natural catchments under assumption of stationarity. Thus, the reliability of hydrological forecasting in human-influenced systems is compromised. Given the large populations exposed to water-driven hazards, there is an urgent need for research and innovation.

This session will highlight recent advances in understanding and forecasting hydroclimatic extremes in human-influenced catchments. We invite abstracts on (but not limited to):
• Development and application of statistical, process-based, machine learning, or hybrid models to forecast hydrological variables at multiple scales
• Advances in data acquisition capturing human activities (or proxies), including in-situ monitoring, remote sensing, and social media, with innovations in data integration and analytics
• Integration of data collected from public and through citizen science to improve the prediction of hydrological extremes
• Novel quantitative methods to assess diverse human impacts on hydrological processes and water cycle
• Coupled human-natural system modelling and scenario analysis to capture feedbacks between socio-economic drivers and hydrological processes
• Impact-based risk assessments of water-related hazards, spanning economic, health, social, and environmental dimensions
• Uncertainty quantification and risk analysis of singular and compound hydro-hazards under non-stationarity
• Enhanced visualization and communication for early warnings and short- to long-range predictions, including projections of unprecedented extremes
• Integration of nature-based solutions and adaptive management strategies into forecasting and risk reduction frameworks

This session focuses on recent advances in probabilistic modelling and ensemble forecasting of streamflow and other environmental variables using machine learning (ML) and deep learning (DL) approaches. Contributions are invited on uncertainty quantification, probabilistic prediction, ensemble generation and post-processing, the use of meteorological and climate data for both model training and real-time forecasting, and decision-support frameworks applicable in contexts of limited information and uncertainty. Topics include hybrid process-based and ML/DL models, explainable AI, foundation models, ensemble learning, mixed-model approaches, and operational forecasting systems. Applications may address streamflow, floods, droughts, water quality, sediment transport, groundwater, ecohydrological variables, and other climate-sensitive environmental processes. Emphasis is placed on reducing, explaining, and communicating predictive uncertainty, and on the use of ensemble and probabilistic models in risk-informed operational decision-making. Participations that clarify the relationship between ensemble spread and predictive uncertainty, or that benchmark probabilistic methods against each other, are particularly welcome.

This session addresses advances in climate and hydro-meteorological forecasts and projections, and their role in predicting water availability and servicing water sectors. It welcomes, without being restricted to, presentations on:

Developing the climate and hydro-meteorological forecast services:

• Seamless prediction and projection systems spanning real-time, sub-seasonal, multi-annual, decadal and long-term timescales for water availability and hydrological extremes (floods, droughts, compound events);
• Process-based, data-driven, AI-enabled, machine learning, and hybrid forecasting methods;
• Methods for post-processing and refining hydro-climate information (e.g., downscaling, bias correction, spatiotemporal disaggregation, blending and interpolation);
• Uncertainty propagation, forecast verification, sensitivity analysis and tools;
• Co-development of forecasts between scientists and service providers.

Applying the climate and hydro-meteorological forecast services:
• Assessment of forecast value, skill and usability for decision-making, including communication, visualization and user engagement;
• Operational hydro-meteorological forecasting systems and hydro-climate services;
• Case studies and water management applications based on these services (e.g., river/reservoir operation, agricultural, industrial and public water use).

The session will bring together researchers, service developers and operational managers in hydrology, meteorology and climate, to share advances, experiences and lessons learned in translating hydroclimate information into practical decision support. Contributions are encouraged from across sectors including water resources management, drinking water supply, transport, energy production, agriculture, disaster risk reduction, forestry, health, insurance, tourism and infrastructure.

While water plays a critical role in sustaining human health, food security, energy production, and ecosystem services, factors such as population growth, climate, and land use change increasingly threaten water quality and quantity. The complexity of water resources systems requires methods integrating technical, economic, environmental, legal, and social issues within frameworks that help design and test efficient and sustainable water management strategies to meet the water challenges of the 21st century. System analyses adopt practical, problem-oriented approaches for addressing the most challenging water issues of our times. These include competing objectives for water, multi-stakeholder planning and negotiation processes, multisector linkages, and dynamic adaptation under uncertainty. This session will feature state-of-the-art contributions to water and multisector resource system management solutions under uncertainty.

The ongoing and projected intensification of the water cycle under uncertain future conditions represents a significant global challenge that necessitates adaptive, robust, and inclusive adaptation strategies. Climate change is causing increased frequency and severity of extreme weather events such as floods and droughts, making it difficult to predict and manage water resources since historical data is no longer a reliable guide for future conditions. Growing urban populations demand more water and can outpace water infrastructure development, leading to shortages and inequities in water distribution, often exacerbated by political, economic, and social factors that influence water governance. The pace of technological change in water treatment, distribution, and conservation can improve the efficiency of water systems management, but it introduces uncertainty regarding their long-term viability and integration into existing human-water systems.

Decision Making Under Deep Uncertainty (DMDU) represents a promising approach to help decision-makers confront such a wide range of unpredictable and variable future conditions. Unlike traditional frameworks that depend on accurate predictions and precise probabilities, DMDU accepts that the future is inherently unpredictable, especially in complex systems like human-water systems, and emphasizes adaptive planning that evolves with new information on water supply, demand, and ecosystem health. This session aims to gather scientists to discuss and exchange knowledge of existing and emerging approaches for supporting the design and implementation of adaptive and robust water management strategies under deep uncertainty. We welcome contributions focused on recent methodological advances, including uncertainty and sensitivity analysis, scenario generation techniques, robust optimization, and experiences related to real-world applications.

Hydrological observations, forecasting and advanced mathematical modelling provide essential tools for integrated water resources management (IWRM). Their practical value depends on how well they address management needs, represent competing objectives and account for ecological, social and institutional conditions. This session brings together hydrological science, systems analysis and practical surface water management to explore how scientific knowledge translates into implementable decisions. Aligned with the IAHS ICWRS scope and the HELPING decade, it connects technical advances with the participation, governance and capacity needed to put them into practice. We invite methodological contributions, comparative analyses and case studies addressing:
• Integration of hydrological modelling, forecasting, simulation and optimization into water allocation, reservoir operation, ecosystem restoration and climate adaptation;
• Problem framing and assessment of trade-offs among technical performance, ecological needs and societal priorities;
• Co-development and use of decision-support tools with managers, communities and policymakers, including local knowledge and uncertainty communication;
• Institutional capacity, economic constraints and governance arrangements influencing implementation, including transboundary settings;
• Evaluation of management outcomes, unintended consequences and transferable lessons from successful, delayed or unsuccessful interventions.
Contributions should connect analytical methods with a concrete decision context and explain the conditions affecting their use. We particularly welcome studies examining both the technical performance of proposed solutions and their practical uptake, distinguishing anticipated benefits from demonstrated outcomes. The aim is to understand how modelling capabilities and implementation conditions together support effective, equitable and adaptive water management.

Adapting to societal challenges, such as climate change, increasing water scarcity and hydrological extremes, while advancing towards the Sustainable Development Goals, requires dynamic transition pathways across various integrated systems (water, transport, energy, food, ecosystems, etc.). Evaluating how such transition pathways play a role for water management and policy calls for modeling approaches that account for interactions and feedbacks between human decisions and natural systems represented by MultiSector Dynamics (MSD) models and approaches.
The role of individual and collective human agency is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, vulnerability and resilience of these systems. Yet, the representation of human decision making in MSD and other coupled human and natural systems models is often highly abstracted and simplistic. Additionally, MSD models tend to ignore or largely abstract institutional dynamics in resource systems, commonly adopting rules that implicitly presume centralized, non-adaptive management of resources and infrastructure limiting our ability to understand how heterogeneous actors and institutions respond and adapt to climatic, hydrological, and societal change, and how these responses feedback across systems.
This session seeks to address these limitations, providing a forum for interdisciplinary exchange around the representation of human actors and action, emerging modeling approaches, and new insights across a wide range of MSD challenges for water management and policy. We thereby aim to contribute to a broader community spanning MultiSector Dynamics, socio-hydrology, human–water systems, water resources systems analysis, focused on advancing our understanding of the role of human agency in coupled human and natural systems facing environmental risks and the need for societal transformations. We broadly invite submissions across disciplinary and methodological modeling approaches (e.g., agent-based, economic, optimization, system dynamics, data-driven, AI/ML/generative, etc.) and domains (water, energy, transport, food, land, ecosystems, etc.). We particularly invite contributions that advance methodological approaches for representing heterogenous adaptive human actors and institutions within coupled human–natural system models, and for linking these representations and their management and policy implications across sectors and scales.

The climate crisis, land use change and over consumption are altering the water cycle beyond a safe planetary boundary. The so-called conventional water, i.e. snowfall, rainfall, river runoff and easily accessible groundwater, is often insufficient to meet growing demands for water and food. Sustainably increasing water availability, allocating water in an equitable way, and adapting to a changing climate are challenges that need to be urgently addressed. A promising option is to use Non-Conventional Waters (NCW), which include ancestral and modern techniques to generate, harvest, store, treat, distribute and use water. The effectiveness of such solutions has already been proven in many parts of the world, but their potential is under-recognized, limiting their widespread adoption, mainly due to socio-economic and governance barriers. This session welcomes studies on non-conventional water resources spanning technical, socio-economic and political disciplines.
More specifically, we accept contributions including, but not limited to:
innovative methods to design, monitor and assess NCW;
social, economic, environmental and cultural sustainability of NCW water use;
good practice examples for NCW solutions implementation;
global and local drivers and barriers to NCW implementation
technical innovations in harvesting, storing, treating, and using NCW, and innovation valorization and transfer;
Stakeholder engagement and multi-actor platforms for NCW planning and implementation
Co-organized by the IAHS Working Group on “Non-Conventional Water Use for Integrated Water Resources Management” of the International Association of Hydrological Sciences: https://iahs.info/Initiatives/Scientific-Decades/helping-working-groups/non-conventional-water-ncw-use-for-integrated-water-resources-management/

Water security is increasingly under threat from accelerating climate change and anthropogenic pressures, with particularly severe implications for Africa and other water-stressed and climate-vulnerable regions. Climate variability, recurrent droughts and floods, urbanisation, agricultural expansion, ecosystem degradation, population growth, and competing water demands are placing increasing pressure on hydrological systems. Persistent inequalities in water access and allocation further highlight the need to move beyond understanding water challenges towards translating scientific knowledge into equitable and effective action.

This session explores how water science, governance, innovation, capacity development, and multi-stakeholder cooperation can bridge the gap between knowledge and implementation that contribute to equitable and climate-resilient water security. Attention is given to connecting scientific evidence with policy frameworks, institutional capacity, local knowledge, and practical implementation, while advancing integrated and multisectoral water resources management.

We invite interdisciplinary and transdisciplinary contributions addressing water security under climate and societal change, with a particular focus on Africa and broader relevance through transferable lessons. Contributions may include: climate-resilient and equitable water resources management; water governance, institutions, policy implementation and allocation; drought, floods and adaptation; multisectoral approaches to competing water demands; water–agriculture–food–ecosystem interactions; participatory approaches and indigenous and local knowledge; innovative monitoring, Earth observation, modelling and decision-support tools; economic and institutional dimensions of water security; and capacity development strengthening the science–policy–practice interface.

The session seeks to identify context-sensitive and scalable pathways from water science to water security by connecting scientific knowledge with governance, institutional strengthening, policy and implementation. Through cross-disciplinary, cross-sector, and cross-scale dialogue, it aims to generate actionable insights for more equitable, cooperative, and climate-resilient water management amid global change.

How do global changes in climate, land use and development translate into water security challenges for particular places, and how can local research and responses, as well as stakeholders' perspectives, inform wider understanding and action? This session will explore connections among global, regional, and local perspectives on water availability, water quality, water-related hazards, equitable access, and ecosystem health.

We bring together hydrology, environmental science, engineering, ecology, geography and social science to examine water security across scales. We welcome conceptual, methodological and empirical contributions connecting large-scale assessments with catchment-, urban- and community-level research.

Topics of interest include:
- Interactions between global environmental change and local water security;
- Multi-scale observation, modelling and assessment;
- Connections between scientific evidence, community knowledge and water management;
- Adaptation and management across scales;
- Comparative studies and synthesis examining how water security challenges and responses differ across climatic, socioeconomic and institutional contexts, and what can be learned or transferred between them.

We encourage contributions from diverse settings worldwide, including Africa, Asia, South America and Europe, across urban, peri-urban and rural environments. Interdisciplinary and transdisciplinary studies as well as collaborations with practitioners and communities are particularly welcome. Single-location studies are also welcome where connections across scales or wider implications are made explicit. The aim is to advance dialogue between global and local research and identify opportunities for shared learning and more effective water management.

There has been substantial progress in improving water, sanitation and hygiene (WASH) access globally. However, many communities continue to face barriers in accessing WASH services, leading to adverse health and safety outcomes, negative impacts on livelihoods, and reduced social and economic development. While much of WASH equity discourse centers on low- and middle-income countries (LMICs), marginalized populations in high-income countries (HICs), including racial and ethnic minorities, people experiencing homelessness, rural communities, and Indigenous groups, still lack consistent, affordable, and safely managed WASH services despite near-universal coverage. Achieving equitable WASH access globally creates opportunities for bidirectional learning and cooperation across geographies and disciplines.

This session explicitly welcomes contributions from both HIC and LMIC contexts, as well as work that compares or connects them. We also invite submissions from a wide range of disciplines, including engineering, public health, epidemiology, economics, law and policy, anthropology, sociology, geography, urban planning, and data science. We especially encourage research grounded in community-engaged and participatory methods, and collaborative frameworks that center lived experience. Through these discussions, we hope to pave the way toward an equitable WASH future for all.

This session welcomes abstracts that consider how to observe, analyse and model feedbacks between social, political and economic processes and hydrological and other environmental processes. The session is organised by the International Commission on Human-Water Feedbacks (ICHWF) of the IAHS, which provides a home for interdisciplinary research on the dynamics of human-water systems, particularly involving the social sciences.
Relevant topics include but are not limited to:
• Observations of human impacts on, and responses to, hydrological change
• Interactions of communities with local water resources
• Hydrological models that include anthropogenic effects
• Interdisciplinary qualitive and quantitative methods
• Theoretical models to isolate, conceptualize and/or simulate feedbacks in human-water systems
• Critical reflections on inter- and transdisciplinary projects (problem framings, roles, methods, exclusions, suggested interventions)
• Creation of databases describing the hydrology of human-impacted systems
• Data analyses and comparisons of human-water systems around the globe and especially in the global south
• Human interactions with hydrological extremes, i.e. floods, droughts and water scarcity
• The role of gender, age, and cultural background in the impacts of hydrological extremes, risk and risk perception, and during/after crises and emergencies

In the Anthropocene, water resources are under unprecedented stress. To address these challenges and develop actionable, sustainable solutions, we need a thorough understanding of not only the hydrological cycle but also its interactions with other complex physical systems and social dimensions. To do this effectively, we need to move beyond a “science-as-usual” approach and leverage transdisciplinary knowledge. This includes actors such as scientists, policymakers, local communities and indigenous peoples, NGOs and local associations, media, and businesses. Each of these brings a unique perspective and expertise, and we must value their contributions not simply as sources of information or data, but as knowledge holders and active contributors to problem framing, knowledge production, solution development, and decision making.

Practices such as co-creation can help bring these different forms of knowledge into dialogue, make assumptions and uncertainties explicit, identify conflicts and synergies, and collectively explore alternative pathways towards, to arrive at integrated solutions for complex water management issues. This vision fits within the framework of the IAHS HELPING decade, which emphasises bottom-up approaches that recognise and empower local stakeholders and local know-how.

This session welcomes studies on co-creation approaches in hydrology and water resources management. More specifically, we welcome studies including, but not limited to: experiences and case studies of participatory and co-creation approaches applied to hydrology and water resources management; co-modelling approaches and socio-hydrological studies involving participation of stakeholders; the role of digital technologies and artificial intelligence in facilitating or transforming co-design; meta-analyses, review of other experiences, and literature reviews; critical geography, political ecology, new conceptual frameworks, and other critical approaches to co-creation and stakeholders involvement in water resources decision making.

Co-organised by the Working Groups on Co-Creation of Water Knowledge and Citizens and Hydrology (CANDHY) of the International Association of Hydrological Sciences:
https://iahs.info/Initiatives/Scientific-Decades/helping-working-groups/co-creating-water-knowledge/
https://iahs.info/Initiatives/Working-Groups/Candhy/

The management and utilization of water storage systems, including dams, reservoirs, natural lakes, and connected groundwater storage, have historically played a central role in securing water supply during dry periods and supporting domestic, industrial, agricultural, energy, and ecological needs. However, increasing water demand, climate change, and intensifying hydroclimatic extremes are placing growing pressure on both natural and human-made storage systems. Projected warming is expected to alter reservoir inflows, evaporation, storage efficiency, water quality, sediment dynamics, and ecosystem functioning, while more frequent droughts, heatwaves, wildfires, and extreme precipitation may generate compound and cascading risks. These pressures increasingly require water storage systems to be managed not in isolation, but as interconnected components of wider river basin and landscape systems.
This session invites theoretical, experimental, observational, and applied studies investigating the future of natural and human-made water storage under local and global environmental change. The session aims to bring together contributions using remote sensing, in situ observations, water resources systems modeling, AI, digital twins, and decision-support approaches to improve the monitoring, prediction, adaptive operation, and long-term sustainability of freshwater storage systems.
Key topics include:
• Impacts of climate variability and change on the need for water storage, reservoir performance, and water availability;
• Sedimentation, water quality, and ecological consequences of reservoir operation and trade-offs among water supply, hydropower, irrigation, flood protection, ecosystems, and other users;
• Reservoir operations modeling and Multi-reservoir and basin-scale management under changing climatic and socio-economic conditions;
• Remote sensing, AI, digital twins, forecasting, and decision-support tools for monitoring and adaptive reservoir operation;
• Governance, policy, and socio-economic dimensions of sustainable water-storage management;
• Case studies demonstrating innovative adaptation strategies and restoration initiatives.

Ancient and traditional hydraulic systems record and store valuable information about the long-term interactions between humans, water, and climate. Underground aqueducts and qanats, reservoirs, terraces and irrigation systems demonstrate ancient societies’ deep understanding of hydrology, hydraulics, and waterscapes; moreover, they unveil their advanced sustainable water management practices and their ability to adapt to changes in climate and environmental conditions, and to the complexities of hydrosocial dynamics. Their preservation offers unique opportunity to examine how human-water interactions have evolved over millennia, how ancestral water knowledge has been transferred (or lost) across generations, and how this knowledge can be preserved and used to inform contemporary water pressures, and sustainable goals.

This session invites interdisciplinary approaches to multi-temporal hydraulic systems beyond an archaeological perspective. We welcome contributions that view of these systems holistically, as living systems, environmental and climate archives, and the repositories of ancestral water knowledge and hydrosocial dynamics. Contributions may address, but are not limited to:

-Design, construction, operation, maintenance, adaptation, and continued use;
-Geospatial and other emergent technologies to document, map, reconstruct, and monitor hydraulic landscapes;
-Social dynamics surrounding water infrastructure, including ancient, traditional, and local knowledge and their intergenerational transfer or loss;
-Contemporary pressures, including groundwater depletion, water pollution, agriculture, land-use change and climate change;
-Lessons from ancient hydraulic practices for water security, climate adaptation, community resilience, and sustainable water management; and
-Integration of archaeological, hydrological, hydrogeology, geospatial approaches with ancient, traditional, and local knowledge to understand socio-hydrology and coupled human–water systems and inform public policies.

The session brings together the fields of anthropology, archaeology, hydrology, hydrogeology, environmental sciences, and emerging geospatial technologies to explore how knowledge from the past, combined with contemporary science and technology, can offer new perspectives for sustaining knowledge transfer, addressing water pressures, and in informing future water policies.

Gradual hydrological change, including groundwater decline, altered flow regimes, wetland loss, snow and glacier retreat and salinization, can be normalized within a generation, so that communities, institutions and scientific assessments judge present conditions against progressively altered reference states. This shifting baseline problem has two components that are rarely examined together: the physical reference condition, reconstructed from instrumental, documentary, paleohydrological and Earth observation records, and the perceived reference condition held by water users and decision makers. Human observations can match instrumental records on the direction of change, yet the generational divergence between perceived and reconstructed hydrological baselines is seldom quantified, and the choice of reference period is often treated as a technical default even where multidecadal variability makes any single window unrepresentative.
This session invites contributions that link evidence of long-term hydrological change to the reference conditions perceived or used by people and institutions, including:
(1) reconstruction of hydrological reference conditions from long records, and the sensitivity of trends, impact estimates and restoration targets to the choice of reference period under low-frequency hydroclimatic variability;
(2) quantitative comparison of perceived or reported reference conditions with reconstructed ones, using surveys, interviews, local and Indigenous knowledge, archives or media records, and of how time since the last major event or past water and land-use decisions bias perception;
(3) representation of changing reference conditions, expectations and learning in socio-hydrological and agent-based models, including memory decay rates calibrated with survey, panel or archival data.
(4) evaluation of whether monitoring, visualization, climate services or participatory approaches make gradual change perceptible, slow the decay of awareness and alter decisions, including panel, longitudinal or experimental studies reporting null or adverse effects.
(5) consequences of baseline choice for water allocation, adaptation and restoration, including whose reference conditions are recognized.
Contributions should connect at least one physical record of change with how reference conditions are perceived, modeled or used in decisions. Studies from data-scarce regions are particularly encouraged.

Water sustains societies, economies, and ecosystem services locally and globally. Yet, competition over freshwater is intensifying worldwide, driven by rising demand and shifting availability under climate change and variability. Addressing these challenges requires integrative water management and policy approaches that balance trade-offs across social, economic, and environmental water uses. Equally, adaptive and flexible solutions are needed to allow policies to adapt to changing and uncertain climatic and socio-economic conditions, thereby strengthening the sustainability and resilience of water systems. This session provides a forum for showcasing novel and emerging research at the intersection of agricultural production, energy security, water supply, economic development, and environmental conservation. In particular, we encourage contributions that: (i) advance understanding of critical interconnections, feedbacks, and risks within water system components, (ii) introduce novel methods or tools for evaluating and monitoring trade-offs and performance in water allocation, management, and policy across sectors, (iii) evaluate technological, policy, and/or governance innovations to address the water-food-energy-environment nexus across scales (local, regional, and/or global), and (iv) advance methods to evaluate risks to water systems and identify solutions to enhance system and user resilience. We welcome real-world examples on the successful application of these methods to facilitate integrated planning and management of the water-food-energy-environment (WEFE) nexus.

Hydropower is a mature and cost-competitive renewable energy source, which helps stabilize fluctuations between energy demand and supply. The structural and operational differences between hydropower systems and renewable energy farms may require changes in the way hydropower facilities operate to provide balancing, reserves or energy storage. Yet, non-power constraints on hydropower systems, such as water supply, flood control, conservation, recreation, navigation may affect the ability of hydropower to adjust and support the integration of renewables. Holistic approaches that may span a range of spatial and temporal scales are needed to evaluate hydropower opportunities and support a successful integration maintaining a resilient and reliable power grid. In particular, there is a need to better understand and predict spatio-temporal dynamics between climate, hydrology, and power systems.

This session solicits academics and practitioners contributions that explore the use of hydropower and storage technologies to support the transition to low-carbon electricity systems. We specifically encourage interdisciplinary teams of hydrologists, meteorologists, ecologist, power system engineers, and economists to present on case studies and discuss collaboration with environmental and energy policymakers.

Questions of interest include:

- Prediction of water availability and storage capabilities for hydropower production

- Prediction and quantification of the space-time dependences and the positive/negative feedbacks between wind/solar energies, water cycle and hydropower

- Energy, land use and water supply interactions during transitions

- Policy requirements or climate strategies needed to manage and mitigate risks in the transition

- Energy production impacts on ecosystems such as hydropeaking effects on natural flow regimes.

This session has the support of the a) Cost Action : Pan-European Network for Sustainable Hydropower (PEN@Hydropower), and b) European Energy Research Alliance (EERA), that established the joint program “Hydropower” to facilitate research, promote hydropower and enable sustainable electricity production. Further information can be found here:
https://www.pen-hydropower.eu/
https://www.eera-set.eu/eera-joint-programmes-jps/list-of-jps/hydropower/

Hydroclimatic extremes, ranging from prolonged droughts to intense wet spells and flooding, are intensifying worldwide. These changes pose escalating risks to agriculture, water management, and, ultimately, global food security, livelihoods, and societies. Yet, projected changes and their cascading effects are often assessed in isolation, a practice that underestimates systemic risks. A more holistic perspective, that acknowledges uncertainties, interactions, and feedbacks of both droughts and floods, is essential to identify resilient and sustainable transition pathways for complex adaptive systems such as agriculture and other land-use systems.
Farmers are traditionally experts at navigating climate variability, but the increasing severity and frequency of hydroclimatic extremes demand new strategies to mitigate systemic risks. Agriculture plays a threefold role in this context: as a sector heavily affected by climate change, as a contributor to greenhouse gas emissions, and as a key source to implement solutions and adaptation strategies. This interplay both amplifies uncertainties and opens opportunities for transformative adaptation. Understanding how individual farmers, farming communities, and agricultural governance actors evaluate risks and adjust practices under dynamic and uncertain conditions is central to clarifying how decisions at different spatial and temporal scales may trigger, accelerate, or prevent broader regime shifts.
This session invites contributions from across the natural and social sciences to explore the multifaceted interactions between hydroclimatic extremes and agriculture. We particularly welcome studies that:
• Provide observational evidence, case studies and methodological advancements on the interplay between climate extremes, agriculture and other land use systems.
• Advance theoretical and conceptual perspectives on connected, compound, and cascading risks and uncertainties.
• Apply nexus approaches, integrating environmental, socio-economic, and governance dimensions.
• Share participatory, co-production, or transdisciplinary approaches engaging farmers, communities, and other stakeholders, including practical tools and interventions.
• Examine decision-making processes and responses at the farm, community, and governance levels, including adaptation strategies and barriers across spatial scales.
• Explore agricultural adaptability, transformation pathways, and potential regime shifts under climate extremes.

Climate change and unsustainable water management practices are driving the world beyond water scarcity. Many areas in arid and semi-arid regions such as the Middle East, Central Asia, and Southern Africa are moving into an era of “water bankruptcy”. Shared aquifers and river systems are under growing pressure from reduced rainfall, accelerated glacier melt, and upstream interventions, intensifying competition for already limited resources. Moreover, many inland terminal lakes, such as the Aral Sea, Lake Chad and Lake Urmia, are drying up, further exacerbating the environmental and socio-economic impacts of the water crisis. In addition, gaps in data availability and technical capacity hinder effective water governance, making transboundary cooperation even more critical for regional stability and sustainability. To address these challenges, a holistic approach is required - one that integrates the Water-Energy-Food-Ecosystem (WEFE) Nexus to foster benefit-sharing between riparian states. By recognising the interdependencies among water resources, energy production, and food security in relation to environmental needs, WEFE Nexus studies offer valuable strategies for optimising resource allocation, reducing competition, and encouraging cooperative solutions across borders.
Furthermore, ongoing digitalisation, AI and real-time monitoring, and advances in data-driven decision-making, including Digital Twin technologies, offer opportunities to bridge data gaps and improve water management. As water demand grows across urban, industrial, and environmental sectors, innovative solutions are needed to enhance efficiency, minimize losses, and build climate resilience. Alongside technological solutions, human capacity building plays a central role in addressing these complex challenges.

The Water-Energy-Food-Ecosystem (WEFE) Nexus provides a systemic understanding of cross-sectoral interdependencies, trade-offs and synergies. Yet, translating it into knowledge and tools that can effectively inform policy and collective decision-making remains challenging. This session aims to explore how transdisciplinary approaches can help move WEFE Nexus research from systems analysis towards policy, decision-making and action.Consistent with the HS context, particular attention will be given to approaches that explicitly examine the relationships between water and the other Nexus dimensions. We particularly welcome approaches that are embedded within transdisciplinary processes and combine scientific and stakeholder knowledge to conceptualise complex systems, explore cross-sectoral feedback and trade-offs, and support the co-development of scenarios, solutions and transition pathways. Emphasis will be placed on real-world case studies in which these approaches have been developed, tested or applied together with stakeholders, rather than on purely theoretical frameworks.
Attention will also be given to the transparency and traceability of modelling assumptions, the validation, and the treatment and communication of uncertainty. Beyond the delivery of technical outputs, we encourage contributions that examine the wider outcomes of transdisciplinary processes, including learning, strengthened systems understanding and capacities, ownership and legitimacy, and their contribution to sustained and adaptive decision-making.
Contributions may address, but are not limited to:
- Integrated modelling approaches for analysing WEFE systems, including System Dynamics Modelling, Agent-Based Modelling, multi-criteria methods and hybrid frameworks;
- Transdisciplinary and participatory approaches to WEFE Nexus research, involving scientists and societal actors in collaborative modelling and knowledge co-production;
- Integration of biophysical, socio-economic, behavioural, institutional and governance dimensions, with explicit attention to the reciprocal relationships between water and the other Nexus components;
- Integration of modelling, monitoring and evaluation to support adaptive WEFE management and decision-making;
- Translation of integrated and participatory assessments into policies, management strategies, adaptation measures and transition pathways;
- Real-world, participatory applications and lessons learned.

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

This session aims to provide researchers with a platform to present and discuss the application, knowledge gaps and future research directions of urban GI and how sustainable green solutions can contribute towards an integrated and sustainable urban hazard management approach. We welcome original research contributions across a series of disciplines with a hydrological, climatic, soil sciences, ecological and geomorphological focus, and encourage the submission of abstracts which demonstrate the use of GI at a wide range of scales and geographical distributions.

We invite contributions focusing on (but not restricted to):
· Monitored case studies which provide an evidence base for integration within a wider hazard management system;
· GIS and hazard mapping analyses to determine benefits, shortcomings and best management practices of urban implementation;
· Laboratory-, field- or GIS-based studies which examine the effectiveness or cost/benefit ratio of solutions in relation to their wider ecosystem potential;
· Methods for enhancing, optimising and maximising system potential;
· Innovative and integrated approaches or systems for issues including bioretention/stormwater management, pollution control, carbon capture and storage, slope stability, urban heat exchange and urban food supply;
· Catchment-based approaches or city-scale studies demonstrating opportunities at multiple spatial scales;
· Rethinking urban design and sustainable, resilient recovery following crisis onset;
· Engagement and science communication to enhance community resilience.

Urban and urbanizing watersheds are among the most dynamic landscapes on Earth, where land use change, population growth, infrastructure development, and evolving water demands reshape hydrological processes, water quality, and catchment functioning. Understanding watershed responses across the urbanization continuum is essential for advancing hydrological science, improving prediction, and informing integrated water and land management.
This session welcomes contributions on urban watersheds across a range of topics, including but not limited to: catchment functioning and responses to land use change; runoff generation, hydrological extremes, and urban drainage processes; water quantity and quality; the sources, transport, transformation, and fate of anthropogenic inputs; urban groundwater and surface water–groundwater interactions; urban water supply and source-water protection; stormwater and wastewater management, blue-green infrastructure, and other nature-based approaches for urban water management; and ecological responses and ecosystem services in urban waters.
We particularly encourage contributions grounded in field studies and monitoring networks in urban settings, including long-term and high-frequency observatories, sensor networks, tracer and isotope studies, citizen science and community-based monitoring, and paired or nested catchment designs, that advance process understanding, calibrate and validate models, or inform the design of urban water management strategies. Contributions linking such field-based approaches with remote sensing, modeling, data assimilation, and data-driven and machine-learning approaches are welcome, as are studies on urban water infrastructure, governance, community engagement, socio-hydrology, and adaptive water and land management.
We encourage contributions spanning a range of climatic, geographic, and socio-economic settings, as well as studies across different stages and forms of urbanization, particularly comparative studies that help identify knowledge gaps in urban watershed processes and management challenges.

The field of socio-hydrology and hydro-social research emerged as an attempt to better understand the dynamic interactions and feedbacks within diverse coupled human-water systems and its implications for the assessment and management of water resources and associated risks.

An integrated perspective offers novel entry points for a more fertile engagement between hydrological and social sciences across different scales ranging from the plot level to entire watersheds, encompassing both surface water and groundwater. Its interdisciplinary nature involves (and integrates) various methodological approaches, epistemologies, and disciplines.

We welcome contributions from researchers from social and natural sciences who are keen to look beyond their research perspective and who like to discuss their research findings in a broader context of coupled human-water systems. Papers should

1) contribute to the understanding of complex human-water interactions and their management,
2) discuss the benefits and shortcomings of different inter- and disciplinary perspectives based on empirical, conceptual or model-based research; and
3) shed light on the added value of socio-hydrological modelling and hydro-social analysis for water resources management, risk management and adaptation design.

We specifically welcome contributions which reflect how the hydro-social and socio-hydrological research approach supports the new IAHS decade HELPING Science for Solutions aim.
This session is co-sponsored by the IAHS under the umbrella of the ICHWF - Commission on Human-Water-Feedbacks.
We are happy to have TBA as a solicited speaker.

Digital Water strategies - such as artificial intelligence (including the more traditional machine learning, generative, and agentic AI), digital twins, smart sensing, real-time data systems and decision-support tools - are reshaping how human-water systems are observed, interpreted, modeled, and managed. Their value, however, depends on how effectively they can support (and explain) better decision-making, improve operational planning and strategic management, and enhance resilience in the face of changing climatic and socio-economic conditions.

This session focuses on both emerging Digital Water methods and the pathways through which data and models become actionable. We welcome contributions on new technological and methodological approaches, including behavioral and human-in-the-loop models that represent how individuals, stakeholders, and institutions respond to information, incentives, risks, and changing water conditions. Relevant topics include AI, data-driven and hybrid modeling, digital twins, behavioral modeling, decision-support systems, and human–model interaction, stakeholder engagement and co-production, and institutional dynamics and governance - including data governance, responsible data sharing, accountability, responsibility, and decision authority in digitally supported water governance. Further topics include equity and human values in water decisions, as well as dealing with uncertainty, explainability and interpretability, bias, and implementation barriers.

Applications may span water supply and demand, drought and flood risk, water quality, infrastructure planning and operation, water allocation, conservation, and climate adaptation. The session aims to advance both innovative Digital Water approaches and understanding of how they shape behavior, decisions, governance, and resilience in human-water systems.

Resilience to both short-term disruptions and long-term systemic changes, both anticipated and unanticipated, has become a focal point of attention in both research and policy over recent years in response to a wide range of challenges. This is equally true for the water industry as for society as a whole. With long-lived infrastructure and a traditionally conservative attitude, resilience building may be particularly challenging in the water industry. Building resilience is a multifaceted challenge, including technical, organizational, financial and governance aspects. A comprehensive approach to resilience encompasses all of these, and is therefore by definition transdisciplinary.
Actionable theoretical frameworks have been proposed in recent years, as well as many initiatives with practitioners.This session seeks to bring these together and explore how a coherent and comprehensive resilience strategy that spans multiple dimensions can be developed and operationalized for drinking water, wastewater and stormwater management. As such, contributions are solicited from both a) researchers studying system resilience in a practical or conceptual context, seeking to translate their insights into practice and b) practitioners already engaged in operationalizing resilience. In particular, transdisciplinary contributions that consider multiple dimensions and/or involve multiple stakeholders are called for. However, single-dimension contributions are also welcomed as pieces of the transdisciplinary puzzle.

Due to urbanization, population growth, climate variability, and increasing pressure on freshwater resources, water-security challenges in cities are intensifying throughout the worldwide. Wastewater generated in urban areas of most of the countries is rarely reused. For example, only few cities in developing and poor countries are reusing the wastewater. Few developed countries have well developed working models for reuse of wastewater. With technological development in wastewater treatment, urban wastewater is increasingly recognized as a valuable alternative water resource. Recycling and reuse of treated wastewater can reduce freshwater demand, minimize pollutant discharge, strengthen drought resilience, and support the transition towards circular and sustainable urban water systems. Treatment efficiency, emerging contaminants, energy and infrastructure requirements, economic feasibility, regulatory frameworks, public acceptance, potential environmental and health risks are few of the challenges which restrict a developing country to reuse wastewater.
This session invites interdisciplinary contributions addressing scientific, technological, environmental, socio-economic, and governance dimensions of urban wastewater recycling and reuse. Particular emphasis is placed on innovative treatment and monitoring technologies, nature-based and decentralized solutions, resource and energy recovery, removal of emerging contaminants and antimicrobial resistance determinants, risk assessment, water-quality monitoring, fit-for-purpose reuse, and integration of wastewater reuse into urban water management. The session also welcomes studies addressing circular economy approaches, life-cycle and techno-economic assessment, climate-resilient wastewater infrastructure, policy and regulatory frameworks, public perception, and successful case studies from cities across different climatic and socio-economic settings. By bringing together researchers, practitioners, utilities, policymakers, and early-career scientists, the session aims to facilitate knowledge exchange and identify scalable pathways for transforming urban wastewater from an environmental burden into a reliable resource for sustainable and resilient water security.

Climate warming poses a significant risk to seasonal snow water storage, which impacts over a billion people worldwide. Snowpack shrinkage results in a drastic reduction in meltwater supply, a temporal shift in runoff, and a decrease in its seasonal predictability. Therefore, understanding seasonal snow dynamics, the potential changes, and their implications is crucial for effective water resource management.
Remote sensing of seasonal snow is a key tool in this regard, as it provides a wide range of techniques and data across various spatial and temporal scales. This session focuses on studies linking remote sensing of seasonal snow to hydrological applications. The works presented will aim to (i) monitor, model and understand snow-related processes and dynamics (snowfall, melting, evaporation, wind redistribution and sublimation), (ii) quantify the snowpack characteristics (e.g., snow water equivalent, snow grain size, albedo, light-absorbing particles, snow cover area, snow depth and snow density), (iii) assess hydrological impacts of the snowpack dynamics.
We welcome contributions that integrate methods and data from traditional or from emerging technologies, including time-lapse imagery, laser scanning, radar, passive microwave, optical photography, photogrammetry, thermal and hyperspectral sensing. All types of platform and all spatial and temporal scales of studies are welcome, from UAV plot-level studies to global multi-year time series of satellite observations.

We invite presentations concerning the past, present and future of soil moisture estimation, including remote sensing, multi-sensor data fusion, field experiments, land surface modelling and data assimilation, machine learning, and Cal/Val activities, in particular concerning the establishment and use of Fiducial Reference Measurements (FRMs).

Microwave remote sensing has made tremendous progress to provide robust estimates of surface and subsurface soil moisture at different scales. From local to landscape scales, several field or aircraft experiments have been organized to improve our understanding of active and passive microwave soil moisture sensing, including the effects of soil roughness, vegetation, spatial heterogeneities, and topography. At continental scales, a series of passive and active microwave space sensors, such as SMMR (1978-1987), AMSR (2002-), and ERS/SCAT (1992-2000) provided information on surface soil moisture. Current investigations of L-band passive observations with SMOS (2009-) and SMAP (2015-), active C-band observations with the Metop/ASCAT series (2006-) and Sentinel-1 (2014-), L- and S-band observations from the NISAR mission (2025-), and bistatic L-band radar observations from GNSS-R missions such as HydroGNSS (2025-) enable an accurate quantification of the soil moisture at regional and global scales at ever higher spatial resolution.

Operational programmes like Copernicus but also novel developments, such as the upcoming CIMR and ROSE-L, will further enhance our capabilities to monitor soil moisture, and they will ensure continuity of multi-scale soil moisture measurements from agricultural to climate scales.

At the same time, research has put a new focus on establishing rigorous guidelines for the installation, calibration, and operation of in situ soil moisture measurements that are informed by metrological practices, as well as on the development of advanced quality control procedures for an ever growing suit of global in situ soil moisture measurement networks to obtain so-called Fiducial Reference Measurements (FRMs) for soil moisture.

Lastly, machine learning has opened up new opportunities for soil moisture retrieval, downscaling, data fusion, gap filling and data assimilation. For example, data assimilation systems have been complemented with machine learning-based observation operators to assimilate remotely sensed soil moisture using techniques such as neural networks and gradient boosting trees.

The RS-ET community continues to advance the monitoring and understanding of water use and availability across diverse landscapes. These developments increasingly support operational applications in agriculture, water management, climate adaptation, ecosystem monitoring and environmental services. This session provides a forum to share advances, address challenges and explore future directions in remote sensing of ET.

This session focuses on methodological advancements in the use of remote sensing (RS) to improve the quantification of ET across a range of climates and environments. We invite contributions that demonstrate how RS techniques can enhance ET assessment, validation, uncertainty quantification, and prediction in diverse settings including agricultural landscapes, riparian zones, urban areas and forest ecosystems. The session aims to provide an overview of recent developments in RS-based ET estimation from regional to global scales. By applying innovative approaches, we seek to address the challenges of ET quantification and deepen our understanding of water and vegetation dynamics across different landscapes.

With growing societal attention to climate change, drought and flood early warning systems, ecosystem monitoring, biodiversity conservation, and the pursuit of a sustainable future, the demand for accurate estimation, modelling, mapping and forecasting of ET has expanded. We welcome contributions that leverage physically-based and hybrid models, data assimilation and fusion, sharpening algorithms, empirical and statistical methods, as well as artificial intelligence (AI) and machine learning (ML). New spaceborne and airborne sensors are creating opportunities to quantify ET across scales and ecosystems. Cloud computing platforms enable scalable, reproducible analysis through access to large datasets and computational resources. By combining advances in observations, modelling, algorithms and computing, this session aims to advance next-generation ET products and applications for sustainable water management and understanding of the terrestrial water cycle.

We welcome research, commentary and debates on:
• recent developments in RS-based ET estimation
• application of AI, cloud computing and other technological advancements
• Integration of RS, modelling, data assimilation and ground measurements
• validation, calibration, uncertainty quantification and upscaling - challenges & solutions
• future directions in RS of ET.

This session focuses on the hydrogeodetic measurement of water bodies such as rivers, lakes, reservoirs, floodplains, wetlands, and groundwater. The measurements relate to estimating water levels, extent, storage, discharge and runoff through the combined use of remote sensing and in situ observations, and their assimilation in numerical models, data-driven and machine learning approaches, leading to both hindcasts and forecasts.
Detailed monitoring of water bodies plays a key role in assessing water resources, understanding water dynamics, characterising and mitigating water-related risks and enabling integrated and sustainable water resources management of aquatic ecosystems. While in situ measurement networks play a central role in the monitoring effort, remote sensing techniques provide homogeneous spatiotemporal measurements in near real-time with great spatial coverage and long time series. The combined use of in situ observations, remote sensing, machine learning approaches, and numerical modelling can provide new insights into the impact of climate change on water bodies from local to regional and global scales.

During the past three decades, a large number of satellites and sensors has been developed and launched, allowing to quantify and monitor the extent of open water bodies (passive and active microwave, optical), the water levels (radar/laser altimetry), the global water storage and its changes (variable gravity). River discharge, a key variable of hydrological dynamics, can be estimated by combining space/in situ observations and modelling, although it remains still challenging with available spaceborne techniques, particularly in poorly gauged and ungauged regions. Additionally, we welcome studies developing multi-mission integration, data fusion, uncertainty characterisation, calibration and validation, data assimilation, machine learning, and forecasting approaches for water body applications. Interferometric Synthetic Aperture Radar (InSAR) is also commonly used to understand wetland connectivity, floodplain dynamics and surface water level and extent changes.

We also welcome submissions on maturing recent technologies like fully-focused SAR Altimetry, and on the growing exploitation of SWOT observations, providing remarkable hydrology-related opportunities, as well as submissions of pre-launch studies for CRISTAL, Sentinel-3C/3D/3NG/6NG, MAGIC/NGGM, Guanlan, HY-2 and SmallSat constellations e.g., the SMASH concept now called REVALTO.

Remote sensing is a critical tool for data collection and observation of floods and surface water dynamics, especially in regions where field surveys and gauging stations are limited, such as remote or conflict ridden areas and data-poor developing nations. The integration of dynamic variables derived from remote sensing (e.g. water extent, depth and width, river slope and cross sections, flow velocities, land cover and land use) into hydraulic models offers the potential to significantly enhance our understanding of hydrological processes and improve predictive capabilities. Case studies from the Global South are strongly encouraged, as are contributions from ungauged and transboundary basins where satellite observations are the primary record.

This session invites cutting-edge presentations on advancing surface water and flood monitoring and mapping through remotely-sensed data, focusing on:
-Flood and surface water mapping from satellite and airborne sensors, including commercial constellations and emerging observation concepts
-Machine learning, deep learning and foundation models for water body detection and flood segmentation
-Flood mapping in challenging environments such as urban, vegetated, arid, and cloud-persistent regions
-Multi-sensor and multi-frequency fusion for consistent flood extent retrieval
-Flood hazard, risk and impact mapping from Earth observation
-Assimilation of satellite-derived flood extent and inundation maps into hydrological and hydraulic models
-Calibration and validation of hydrological and hydraulic models using remotely sensed observations and field measurements, as well as the creation and use of benchmarks, uncertainty quantification methods, and standards for this purpose
-Monitoring surface water dynamics and change such as seasonal water body variation, wetland extent, river planform
-Operational rapid mapping and emergency response, and the path from research product to sustained service or tool
-Multi-satellite data products and services for improved monitoring of surface water dynamics including floods

Early career and underrepresented scientists are particularly encouraged to participate.

The Surface Water and Ocean Topography (SWOT) satellite mission, launched in December 2022, has marked a significant advancement in hydrological sciences. SWOT uses novel Ka-band radar interferometry to deliver, for the first time, simultaneous, high-resolution measurements of water surface elevation and inundation extent in rivers, lakes, reservoirs, and wetlands globally. SWOT is fundamentally transforming our ability to understand the movement of water across landscapes globally. The hydrology and remote sensing science communities have worked for over a decade to develop new methods and scientific understanding that will allow SWOT data to advance global hydrology. For this session, we solicit abstracts presenting recent advances using data from SWOT to unlock new frontiers in hydrology, inland cryosphere, and estuaries. We also welcome presentations of improved algorithms for extracting hydrologically relevant information from SWOT data, as well as new modeling and data science techniques leveraging data from SWOT combined with other satellite data.

The water cycle or hydrological cycle involves the continuous movement of water on, above, and below the surface of the Earth. In general, hydrological cycle components (e.g., precipitation, evaporation, water storage, and runoff) are characterized by large temporal and spatial variability. Accurate monitoring of various hydrological cycle components and developing hydrological models are important for improving our understanding of hydrological processes. With significant development of sensor technology and sharply growing platforms in past decades, remote sensing offers enhanced capability to monitor various hydrological cycle components at different temporal and spatial scales to complement conventional in situ measurements. Considerable efforts have been made to explore the potentials of remotely sensed data from a vast range of different platforms (e.g., satellite, airborne, drone, ground-based radar) and sensors (e.g., optical, infrared, microwave) in advancing hydrology research, particularly in poorly gauged and ungauged regions. The application of remote sensing in hydrology is expected to increase with enhanced recognition of its potentials and continuous development of advanced sensors (e.g., new satellite missions) and retrieval methods (e.g., innovative machine learning and data assimilation techniques).

The session aims to present and discuss recent advances in the remote sensing of hydrological cycle components as well as the application of remote sensing in hydrological modeling. We encourage studies to investigate the performance of remotely sensed data in multi-variable calibration and spatial evaluation of hydrological models. The added-value of spatially downscaling remotely sensed data in improving hydrological modelling is also particularly welcome.

Water is our planet’s most vital resource, and the primary agent in some of the biggest hazards facing society and nature. Recent extreme heat and flood events underline the significance of water both as a threat and as an increasingly volatile resource.
The accurate and timely measurement of streamflow is therefore more critical than ever to enable the management of water for ecology, for people and industry, for flood risk management and for understanding changes to the hydrological regime. Despite this, effective monitoring networks remain scarce, under-resourced, and often under threat on a global scale. Even where they exist, in-situ observational networks are increasingly inadequate when faced with extreme conditions, and lack the precision and spatial coverage to fully represent crucial aspects of the hydrological cycle.

This session aims to tackle this problem by inviting presentations that demonstrate new and improved methods and approaches to streamflow monitoring, including:
1) Innovative methodologies for measuring/modelling/estimating river stream flows;
2) Real-time acquisition of hydrological variables;
3) UAS and satellite remote sensing techniques for hydrological & morphological monitoring;
4) Measurement in extreme conditions associated with the changing climate;
5) Measurement of sudden-onset extreme flows associated with catastrophic events;
6) Strategies to quantify and describe hydro-morphological evolution of rivers;
7) New methods to cope with data-scarce environments;
8) Inter-comparison of innovative & classical models and approaches;
9) Evolution and refinement of existing methods;
10) Guidelines and standards for hydro-morphological streamflow monitoring;
11) Quantification of uncertainties;
12) Development of expert networks to advance methods.

Contributions are welcome with an emphasis on innovation, efficiency, operator safety, and meeting the growing challenges associated with the changing climate, and with natural and anthropogenically driven disasters such as dam failures and flash floods.

Additionally, presentations will be welcomed which explore options for greater collaboration in advancing riverflow methods and which link innovative research to operational monitoring.

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

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

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

Agriculture is the largest consumer of water worldwide and at the same time irrigation is a sector where huge differences between modern technology and traditional practices do exist. Furthermore, reliable and organized data about water withdrawals for agricultural purposes are generally lacking worldwide, thus making irrigation the missing variable to close the water budget over anthropized basins. As a result, building systems for improving water use efficiency in agriculture is not an easy task, even though it is an immediate requirement of human society for sustaining the global food security, rationally managing the resource and reducing causes of poverties, migrations and conflicts among states, which depend on trans-boundary river basins. Climate changes and increasing human pressure together with traditional wasteful irrigation practices are enhancing the conflictual problems in water use also in countries traditionally rich in water. Hence, saving irrigation water improving irrigation efficiency on large areas with modern techniques is an urgent action to do. In fact, it is well known that agriculture uses large volumes of water with low irrigation efficiency, accounting in Europe for around 24% of the total water use, with peak of 80% in the Southern Mediterranean part and may reach the same percentage in Mediterranean non-EU countries. North Africa region has the lowest per-capita freshwater resource availability among all Regions of the world.
Several studies have recently explored the possibility of monitoring irrigation dynamics and by optimizing irrigation water management to achieve precision farming exploiting remote sensing information combined with ground data and/or water balance modelling.
In this session, we will focus on: the use of remote sensing data to estimate irrigation volumes and timing; management of irrigation using hydrological modeling combined with satellite data; improving irrigation water use efficiency based on remote sensing vegetation indices, hydrological modeling, satellite soil moisture or land surface temperature data; precision farming with high resolution satellite data or drones; farm and irrigation district irrigation management; improving the performance of irrigation schemes; estimates of irrigation water requirements from ground and satellite data; ICT tools for real-time irrigation management with remote sensing and ground data coupled with hydrological modelling.

Increasing climate variability and water scarcity are placing unprecedented pressure on agricultural systems worldwide. To address these challenges, the agricultural sector is rapidly adopting precision technologies that combine remote sensing capabilities with artificial intelligence to optimize crop water management. This session focuses on cutting-edge applications of remote sensing technologies and AI-driven analytics in transforming agricultural water management practices. We welcome research that demonstrates innovative approaches to monitoring, predicting, and managing agricultural water resources by integrating datasets from Earth observation satellites, unmanned aerial systems, Internet of Things (IoT) sensors and using advanced computational methods.
Key topics include:
Multi-platform remote sensing applications (satellite, UAV, hyperspectral, SAR, thermal infrared) for estimation of soil moisture and crop water requirement.
Deep learning and AI-driven detection of crop water stress and yield prediction.
Precision irrigation systems and automated water management technologies.
Multi-sensor data fusion combining space-based, airborne, and ground observations.
Real-time monitoring systems and subseasonal-to-seasonal water demand forecasting models.
Digital agriculture platforms and decision support tools for sustainable water management.
LLM-augmented modeling and digital twin of the agri-climatic or agri-weather landscape.
This session aims to showcase practical solutions that bridge the gap between technological innovation and real-world agricultural applications, emphasizing scalable approaches that support both productivity and environmental sustainability.

Remote sensing products have great potential to support the monitoring and modelling of water resources. Nevertheless, their uptake by water managers remains limited because of concerns related to data quality, spatial and temporal resolution, trust, accessibility, and technical expertise.

In this session, we look for contributions on new developments that support the use of remote sensing data for water-management applications, from local to global scales. We welcome research aimed at improving the quality and usability of remote sensing products, such as higher spatial and/or temporal resolution mapping of land use and agricultural practices; improved assessments of river discharge, lake and reservoir volumes, and groundwater resources; drought monitoring and modelling and its impacts on water-stressed vegetation; and the monitoring and modelling of irrigation volumes.

We are also interested in studies assessing the quality of remote sensing products through uncertainty analysis or validation against independent data sources. Contributions that combine different techniques —such as physically based models and artificial intelligence—or integrate multiple data sources from different sensors, including remote sensing and in situ observations, are particularly welcome. Studies using different types of imagery, including satellite, airborne, and drone data, are also encouraged.

Finally, we invite presentations on the development of user-friendly platforms that follow the FAIR principles and provide smooth access to remote sensing data for water-management applications. We are particularly interested in applications of remote sensing to characterise human–water interactions and assess the impacts of climate change across the entire water cycle, including the connections between inland and sea (coastal) systems.

With the proliferation and wide accessibility of remotely sensed information, data from remotely piloted aircraft (RPA), piloted airplanes, and satellite missions such as Landsat, Sentinel, NISAR and VIIRS are being increasingly used to better our understanding of hydrological processes on the earth’s surface. This understanding is a crucial prerequisite to ameliorate resource management, optimise the development of infrastructure, and adjust land use practices to changing climate conditions and hazards such as floods and droughts. However, many analyses incorporate remote sensing data by default without a thorough critical examination of their applicability and limitations. In-situ data, though expensive to collect and therefore often less readily available, provide a valuable layer of information and a benchmark for methods relying on remotely sensed data.
This session invites contributions that highlight innovative approaches to synthesizing remotely sensed and in-situ data at local-to-regional scales. We welcome contributions that focus on combining multi-scale remote sensing and/or remote sensing with in-situ information and that critically engage this intersection to better understand:
* Processes such as evapotranspiration, infiltration, (Monsoon) inundations, water abstraction for agricultural use
* Hydrological extremes such as floods and droughts
* Improve monitoring and science in poorly gauged and ungauged basins
* Developing novel methods of gathering in-situ benchmark data to combine with remotely sensed approaches

Surface water bodies are critical resources, yet face pressure from environmental changes across scales, ranging from widespread pollution and overexploitation to climate change and land use shifts such as urbanisation. They are further impacted by historical legacies often associated with local human activities (e.g. flood control measures, land cover changes driven by human needs, local pollution). These dynamics operate and interact at different spatio-temporal scales, from local (water quality, flood management, etc.) to global (biogeochemical cycles, etc.). Remote sensing, especially in combination with in-situ data and modelling approaches, is a powerful tool to analyse this complexity, but its integration with governance or policy strategies remains poorly understood and implemented.
This session invites submissions that highlight the potential of approaches combining remote sensing with in-situ data and/or modelling approaches to detecting, assessing, and tracking human impacts within and across watersheds. Submissions highlighting the value of remote sensing for water management and governance at multiple scales are particularly welcome. This can, for example, include studies on:
- Data, methods, and tools for multi-scale analyses of watersheds (combining field data and remote sensing; data or sensor fusion; time series; visualisation approaches)
- Critical appraisals of remote sensing approaches in river science and management (e.g. evaluation of global data products for their suitability for supporting decision making)
- Past, present and future human pressures and their impacts on floodplains and alluvial corridors, notably addressed at large or multiple spatial scales
- Governance, political strategies and regulatory frameworks interacting with remotely sensed data or derived products, which address or facilitate solutions for watershed management and resilience.

The Tibetan Plateau and surrounding mountain regions, known as the Third Pole, cover an area of > 5 million km2 and are considered to be the water tower of Asia. The Pan Third Pole expands on both the north-south and the east-west directions, going across the Tibetan Plateau, Pamir, Hindu Kush, Iran Plateau, Caucasian and Carpathian, and covering an area of about 20 million km2. Like the Arctic and Antarctica, the Pan Third Pole’s environment is extremely sensitive to global climate change. In recent years, scientists from around the globe have increased observational, remote sensing and numerical modeling research related to the Pan Third Pole in an effort to quantify and predict past, current and future scenarios. Co-sponsored by TPE (www.tpe.ac.cn), this session is dedicated to studies of Pan Third Pole atmosphere, cryosphere, hydrosphere, and biosphere and their interactions with global change. Related contributions are welcomed.

Rainfall is a “collective” phenomenon emerging from numerous drops. It reaches the ground surface with varying intensity, drop size and velocity distribution. Understanding the relation between the physics of individual drops and that of a population of drops remains an open challenge, both scientifically and for practical implications. This remains true also for solid precipitation. Hence, it is much needed to better understand small scale space-time precipitation variability, which is a key driving force of the hydrological response, especially in highly heterogeneous areas (mountains, cities). This hydrological response at the catchment scale is the result of the interplay between the space-time variability of precipitation, the catchment geomorphological / pedological / ecological characteristics and antecedent hydrological conditions. Similarly to the small scales, accurate measurement and prediction of the spate-time distribution of precipitation at hydrologically relevant scales still remains an open challenge.

This session brings together scientists and practitioners who aim to measure and understand precipitation variability from drop scale to catchment scale as well as its hydrological consequences. Contributions addressing one or several of the following topics are encouraged:
- Novel techniques for measuring liquid and solid precipitation variability at hydrologically relevant space and time scales (from drop to catchment scale), from in-situ measurements to remote sensing techniques, and from ground-based devices to spaceborne platforms. Innovative comparison metrics are welcomed;
- Drop (or particle) size distributions, small scale variability of precipitation, and their consequences for precipitation rate retrieval algorithms for radars, commercial microwave links and other remote sensors;
- Novel modelling or characterization tools of precipitation variability from drop scale to catchment scale from various approaches (e.g. scaling, (multi-)fractal, statistic, deterministic, numerical modelling);
- Novel approaches to better identify, understand and simulate the dominant microphysical processes at work in liquid and solid precipitation.
- Applications of measured and/or modelled precipitation fields in catchment hydrological models for the purpose of process understanding or predicting hydrological response.
- Rainfall simulators developed to investigate the accuracy of disdrometer measurements in assessing drop size and fall velocity.

The statistical characterization and modelling of precipitation are crucial in a variety of applications, such as flood forecasting, water resource assessments, evaluation of climate change impacts, infrastructure design, and hydrological modelling. This session aims to gather contributions on research, advanced applications, and future needs in the understanding and modelling of precipitation, including its variability at different scales and its sources of uncertainty.

Contributions focusing on one or more of the following issues are particularly welcome:
- Process conceptualization and approaches to modelling precipitation at different spatial and temporal scales, including model parameter identification, calibration and regionalisation, and sensitivity analyses to parameterization and scales of process representation.
- Novel studies aimed at the assessment and representation of different sources of uncertainty of precipitation, including natural climate variability and changes caused by global warming.
- Uncertainty and variability in spatially and temporally heterogeneous multi-source ground-based, remotely sensed, and model-derived precipitation products.
- Estimation of precipitation variability and uncertainty at ungauged sites.
- Modelling, forecasting and nowcasting approaches based on ensemble simulations for synthetic representation of precipitation variability and uncertainty.
- Machine-learning approaches for precipitation modelling, forecasting, and downscaling: Machine-learning and hybrid (physics-informed) methods for precipitation simulation, uncertainty quantification, bias correction, and spatio-temporal downscaling, including baseline comparisons, cross-climate transfer tests, and evaluations of explainability and robustness.
- Scaling and scale invariance properties of precipitation fields in space and/or in time.
- Dynamical and statistical downscaling approaches to generate precipitation at fine spatial and temporal scales from coarse-scale information from meteorological and climate models.

This session is designed to explore the impacts of hydroclimatic variability, climate change, and temporal and spatial availability of water resources on different factors, such as food production, population health, environment quality, and local ecosystem welfare.
We particularly welcome submissions on the following topics:
• Complex inter-linkages between hydroclimatic conditions, food production, and population health, including: extreme weather events, surface and subsurface water resources, surface temperatures, and their impacts on food security, livelihoods, and water- and food-borne illnesses in urban and rural environments.
• Quantitative assessment of surface-water and groundwater resources, and their contribution to agricultural system and ecosystem statuses.
• Spatiotemporal modeling of the availability of water resources, flooding, droughts, and climate change, in the context of water quality and usage for food production, agricultural irrigation, and health impacts over a wide range of spatiotemporal scales.
• Smart infrastructure for water usage, reduction of water losses, irrigation, environmental and ecological health monitoring, such as development of advanced sensors, remote sensing, data collection, and associated modeling approaches.
• Modelling tools for organizing integrated solutions for water supply, precision agriculture, ecosystem health monitoring, and characterization of environmental conditions.
• Water re-allocation and treatment for agricultural, environmental, and health related purposes.
• Impact assessment of water-related natural disasters, and anthropogenic forcing (e.g. inappropriate agricultural practices, and land usage) on the natural environment (e.g. health impacts from water and air, fragmentation of habitats, etc.).
• Assessment of climate mitigation and water impacts on food security and nutrition, especially effects on crop productivity, water availability for irrigation needs, and resilience of food production systems in a variable hydro-climatic environment.
• Nature-based solutions focusing on the connections between water, climate, food, and health, including how to improve water and soil quality, agricultural water productivity, ecosystem services, food systems resilience, and human welfare.
We especially encourage interdisciplinary studies that extend beyond regular hydroclimatic assessments, investigating/exploring their importance to food security and human health.

Scientists are facing several challenges when applying climate models for hydrological variables, such as variety in ensembles, uncertainty or model decisions. Perspectives of climate and hydrological researchers might deviate and a gap exists between the information provided by climate scenarios and the data required for effective hydrological analyses and decision-making. Reducing this gap and improving the assessment of climate change impacts requires a deeper understanding of the interactions between climate drivers and hydrological processes across regional and local scales, as well as more accurate representations of these interactions within modelling frameworks. This is essential for developing reliable forecasts, attributing observed changes and assessing risk posed by extreme events. In this context, uncertainties, probabilistic approaches, and scenario-based predictions must be explicitly quantified and effectively communicated. Addressing these challenges calls for advanced modelling approaches and robust uncertainty quantification methods capable of accounting for both hydrological and anthropogenic influences on the water cycle under present and future conditions.

This session particularly welcomes, but is not limited to, contributions on:
- Advanced methods for the identification, simulation and prediction of hydrological processes and water resources, with emphasis on stochastic, data-driven and hybrid methods;
- Innovative techniques for simulating and forecasting hydroclimatic extremes, including compound and cascading events (e.g. heatwaves, floods and droughts);
- Holistic approaches for developing future water resources scenarios that explicitly incorporate climatic, environmental and anthropogenic drivers;
- Studies on hydroclimatic change attribution using probabilistic approaches and novel causality frameworks with uncertainty assessment;
- Evaluation of climate models performance, uncertainty and variability at regional and local scales using observational data;
- Downscaling of climate projections and related uncertainty propagation into hydrological variables;
- Advances in translating climate projections into actionable hydrological information for water-resource management, risk assessment, and adaptation planning;
- Socio-hydrological scenarios combining climate change, demographic dynamics, and land-use transformations within a coherent modelling framework.

Extreme hydro-meteorological events drive many hydrologic and geomorphic hazards, such as floods, landslides and debris flows, which pose a significant threat to modern societies on a global scale. The continuous increase of population and urban settlements in hazard-prone areas in combination with evidence of changes in extreme weather events lead to a continuous increase in the risk associated with weather-induced hazards. To improve resilience and to design more effective mitigation strategies, we need to better understand the triggers of these hazards and the related aspects of vulnerability, risk, mitigation and societal response.
This session aims at gathering contributions dealing with various hydro-meteorological hazards that address the aspects of vulnerability analysis, risk estimation, impact assessment, mitigation policies and communication strategies. Specifically, we aim to collect contributions from academia, industry (e.g., insurance) and government agencies (e.g., civil protection) that will help identify the latest developments and ways forward for increasing the resilience of communities at local, regional and national scales, and proposals for improving the interaction between different entities and sciences.
Contributions focusing on, but not limited to, novel developments and findings on the following topics are particularly encouraged:
- Physical and social vulnerability analysis and impact assessment of hydro-meteorological hazards
- Advances in the estimation of socioeconomic risk from hydro-meteorological hazards
- Characteristics of weather and precipitation patterns leading to high-impact events
- Relationship between weather and precipitation patterns and socio-economic impacts
- Socio-hydrological studies of the interplay between hydro-meteorological hazards and societies
- Hazard mitigation procedures
- Strategies for increasing public awareness, preparedness, and self-protective response
- Impact-based forecast, warning systems, and rapid damage assessment.
- Insurance and reinsurance applications

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

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

Rainfall for engineering design is usually estimated from records that are short and sparse, variable in space and time, and increasingly affected by changing hydroclimatic regimes that challenge the stationarity assumptions behind traditional Intensity-Duration-Frequency (IDF) and Depth-Duration-Frequency (DDF) estimation. A structural mismatch compounds this: design rainfall must be resolved for the durations, return periods, and spatial scales applications demand, whereas short records, sparse networks, and ungauged sites rarely support these targets directly. Reliable estimation, therefore, needs models that represent rainfall variability across scales while accounting for the storm types and processes shaping extremes.

This session collects recent advances in modelling rainfall for engineering design: new theory, physically based frameworks, statistical and stochastic models, high-resolution observations (e.g., radar, satellite), physics-based simulations (e.g., convection-permitting models), and hybrid methods. Contributions span scales relevant to hydrological and hydraulic applications, from sub-hourly to multi-day durations and from point to areal estimates. Topics include but are not limited to:

– Methodological advances across spatiotemporal scales, including IDF or DDF derivation and use of physical information and covariates;
– Stochastic models, disaggregation, and continuous simulation for design-relevant estimates across scales;
– Areal estimation, areal reduction factors, and point-to-catchment-scale relationships;
– Multivariate analysis of extremes, including tail dependence, process heterogeneity, and cross-duration dependence, translated into joint design quantities and IDF or DDF surfaces;
– Estimation under changing climatic regimes, including covariate-dependent and trend-informed frequency models, and translation of climate-model outputs into design quantities (e.g., bias correction, change-factor and direct methods, ensembles);
– Process- and regime-conditioned estimation, including atmospheric rivers, monsoonal regimes, seasonality, and storm-type classification;
– Regional frequency analysis, pooling, and estimation at ungauged, data-poor sites;
– Emerging data and methods, including radar, satellite, reanalysis, and convection-permitting products, downscaling, machine learning, and hybrid frameworks;
– Design hyetographs, probable maximum precipitation (PMP), and quantification, propagation, and communication of uncertainty.

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

Traditionally, hydrologists focus on the partitioning of precipitation water on the land surface into evaporation and runoff, while ignoring factors that influence precipitation. However, more than half of the evaporation globally returns as precipitation on land. Given this important feedback of the water cycle, changes in land-use and water-use, as well as climate variability and change, impact not only the partitioning of precipitation water but also the atmospheric input of water as precipitation, at both remote and local scales.

This session aims to:
i. investigate the remote and local atmospheric feedbacks from human interventions such as greenhouse gasses, irrigation, deforestation, and reservoirs on the water cycle, precipitation and climate, based on observations and coupled modelling approaches,
ii. investigate the use of hydroclimatic frameworks such as the Budyko framework to understand the human and climate effects on both atmospheric water input and partitioning,
iii. explore the implications of atmospheric feedbacks on the hydrological cycle for land and water management.

Applied studies in this session may adopt fundamental characteristics of the atmospheric branch of the hydrological cycle on different scales. These fundamentals include, but are not limited to, atmospheric circulation, humidity, hydroclimate frameworks, residence times, recycling ratios, sources and sinks of atmospheric moisture, energy balance and climatic extremes. Studies may also evaluate different data sources for atmospheric hydrology and implications for inter-comparison and meta-analysis. Examples of data sources and methodological approaches include observation networks, isotopic studies, conceptual models, Budyko-based hydroclimatological assessments, back-trajectories, reanalysis and fully coupled Earth system model simulations.

Understanding how urban environments interact with hydrometeorological extremes is becoming increasingly important as cities face growing risks from extreme precipitation, flooding, drought, and compound events. The characteristics of these extremes are shaped by interactions among local atmospheric and hydrological processes, land-surface properties, and urban form. Yet these interactions remain difficult to generalise across cities, climates, and spatial and temporal scales. This complexity reflects the high heterogeneity of urban environments and the multiple physical pathways through which urbanisation can influence hydrometeorological extremes. Addressing this challenge requires approaches that can disentangle nonlinear and scale-dependent relationships while retaining physical interpretability.
Machine learning provides opportunities to identify dominant drivers, characterise nonlinear relationships, and reveal spatially and climatically varying responses that are difficult to isolate based on conventional approaches alone. In particular, explainable machine learning (XAI), physics-informed machine learning, causal modelling and hybrid modelling can further support the transition from predictive performance to robust interpretation, hypothesis testing, and process understanding.
This session welcomes studies using machine learning and related data-driven approaches to advance understanding of hydrometeorological extremes in complex urban environments. We particularly welcome studies that use machine learning for physical interpretation, hypothesis testing, and process understanding. Key topics of discussion include:
• Identifying the drivers and nonlinear interactions shaping extreme precipitation, flooding, drought, and compound events.
• Investigating how urban form, land-surface properties, and infrastructure interact with atmospheric and hydrological processes across spatial and temporal scales.
• Applying explainable AI (XAI), physics-informed machine learning, causal modelling, and hybrid approaches to support physical interpretation and process understanding.
• Integrating remote sensing and other multi-source observations to characterise heterogeneous patterns and their scale dependence.

The growing availability of hydrological data products derived from Earth observations, reanalysis systems, numerical models, in situ monitoring networks, and data assimilations has transformed our ability to monitor and understand the terrestrial water cycle.
These products have become indispensable for supporting applications ranging from flood and drought management to water resources planning, agriculture, ecosystem monitoring, and climate adaptation. Yet product selection still often relies on general and often partial performance rankings that may not reflect the requirements of a specific process, scale, hydrological regime, model, hazard, service, or decision. They also may not reflect large differences in the spatial distribution and historical depth of the supporting data.
This session invites contributions that explore how hydrological data products should be assessed, compared, and used to maximize their scientific and societal value, based on the intended application. We encourage discussions on methodologies that go beyond traditional validation and consider aspects such as uncertainty, robustness, consistency across scales, interoperability, usability, and fitness for purpose.
Particular emphasis is placed on understanding how different user communities define product quality and how assessment frameworks can better reflect their needs.
Topics include, but are not limited to:
● Assessment, benchmarking, , and uncertainty assessment of satellite-derived, reanalysis, model-based, and integrated hydrological datasets.
● Fitness-for-purpose assessments of gridded products for scientific analyses, models, operational services, climate applications, and decision-support systems.
● Scale dependence, representativeness, and cross-product consistency.
● Experiences from operational services and real-world applications that reveal strengths and limitations of existing products.
● Case studies demonstrating how dataset choice influences hydrological analyses, forecasts, or management decisions.
● Emerging approaches for evaluating products in the context of digital twins, Earth system modelling, and climate services.
● Analyses or discussions addressing the influence of changes in the constelation(s) of Earth orbiting satellite.
The session welcomes contributions from data producers, hydrologists, remote sensing scientists, model developers, operational agencies, policy experts, and end users.

Multiphase flows play a central role in a broad range of natural and engineered processes, such as nutrient cycles and contaminant remediation in soils, and geological storage of carbon dioxide and hydrogen in deep reservoirs. Understanding multiphase systems across scales is therefore fundamental for water resources management as well energy and climate concerns.

The presence of multiple fluid phases enhances heterogeneity at the level of flow, mixing, and reaction in structurally heterogeneous media. This impacts the transport of dissolved substances and fundamentally changes mixing patterns and effective reaction rates, posing major challenges for predictive modeling. Recent theoretical and experimental advances provide unprecedented insights into the pore-scale mechanisms governing these processes and open new opportunities to tackle these challenges.

This session aims to bring together researchers working on fundamental and applied aspects of flow, transport, mixing, and reaction in multi-phase systems across scales. In particular, we encourage submissions relating to experimental, numerical, and theoretical contributions pertaining to the following topics:

- Impact of medium heterogeneity on multiphase flow, from the pore to the continuum scale.
- Impact of multiphase flow patterns on mixing and reaction rates across scales in heterogeneous media.
- Biogeochemical processes in multiphase systems.
- Applications to vadose zone hydrology and geological storage.

Fractured-porous media and karst systems remain among the most challenging geological media to investigate due to their high heterogeneity and scale-dependent flow and transport properties. Given their abundance, they are important for various research fields such as hydrogeology, geothermal energy, CO₂ storage and nuclear waste repository management, as well as petroleum and mining engineering. Decades of research have explored a broad spectrum of methods, including field experiments, laboratory-scale approaches, analytical techniques and numerical modeling. However, the multiscale nature of these systems requires bridging micro- and macro-scale processes in order to accurately represent flow and (reactive) transport processes. In this session, we therefore welcome contributions that focus on flow and (reactive) transport in karst systems and fractured-porous media. Topics include, but are not limited to: (1) advances in field methods and laboratory techniques to characterize flow and transport from pore to field scales; (2) numerical and analytical modeling approaches for multiscale process understanding; (3) studies targeting the management and efficient use of geothermal, mineral and petroleum resources; and (4) studies targeting water resources management and environmental risk assessment.

The strong nonlinearity of the governing PDEs, coupled with the spatial heterogeneity and anisotropy of the subsurface media parameters, continues to pose significant challenges in mathematical and numerical modeling of subsurface flow and transport processes. These challenges become pronounced under changing climatic conditions, where increasing hydroclimatic variability and extreme events can induce rapid transitions in soil moisture and phase dynamics, flow regimes, and freshwater availability within subsurface environments. The conventional modeling approaches may struggle to adequately resolve these highly transient and nonlinear processes across multiple spatial and temporal scales. In parallel, increasing natural and anthropogenic influences are introducing a wide range of emerging contaminants, such as microplastics, PPCPs, PFAS, and other persistent pollutants, into soil and groundwater systems, whose transport, retention, transformation, and fate in variably saturated subsurface environments have yet to be studied properly. Simulating the complex interactions among these emerging contaminants, soil particles, pore-water chemistry, air-water interfaces, and biological processes further challenges the existing modeling frameworks. Besides, certain complex flow and transport phenomena in subsurface hydrology require problem-specific mathematical formulations and robust numerical strategies to obtain stable, accurate, and physically consistent solutions. This session invites contributions that advance the mathematical, numerical, analytical, statistical, and data-driven modeling of subsurface flow and transport processes. Contributions addressing methodological developments, model applications, laboratory- or field-scale investigations, and multiphysics and multiscale modeling approaches are particularly encouraged. Contributions related to the following topics, and beyond, are welcome:
● Microplastics in vadose zone – insights into pore-scale complexities and modeling strategies.
● Advanced mathematical modeling approaches for transport dynamics of emerging contaminants in variably saturated subsurface environments.
● Coupled modeling of flow, solute transport, and exchange processes between surface and subsurface systems.
● Numerical and analytical modeling of seawater intrusion in coastal aquifers.
● Numerical modeling of non-Darcian flows through subsurface media.
● Development and application of AIML modeling surrogates in subsurface hydrology.

Chemical reactions between fluids and minerals continuously reshape porous and fractured rocks. Dissolution, precipitation, cementation, and mineral replacement alter pore geometry and connectivity, changing the pathways through which fluids and solutes reach reactive sites. The resulting feedbacks between reaction and transport can amplify or suppress heterogeneity and generate recognizable structures across a wide range of spatial and temporal scales. This can be illustrated by acidization wormholes, karst networks, reactive melt channels in magmatic rocks, and diagenetic features such as concretions, reaction fronts and precipitation and/or dissolution patterns.

The underlying challenge is common to all of them: how reactions in individual pores become expressed as large-scale patterns and as changes in porosity and permeability — a question shared across sedimentology, geochemistry, hydrology, petrophysics, and geophysics. It matters wherever reactive flow must be predicted or engineered: carbon storage and mineralization, hydrogen production, geothermal energy, hydrocarbon recovery, nuclear waste repositories, and contaminant transport and remediation.

This field covers approaches, methodologies, and scales of a wide variety. X-ray imaging, microfluidics, and other in situ methods now resolve local mineral reactions as the geometry of the medium evolves. Computational advances bridge pores, fractures, laboratory samples, and field systems. Rock record study shows how these processes accumulate and interact over geological time, on timescales no experiment can reach.

Thereby, we invite contributions on reactive transport and diagenesis from experiments, field observations, theory, and computation. Studies may address dissolution, precipitation, cementation, mineral replacement, authigenesis, water-rock interaction, or biogeochemical transformations. They should investigate the consequences of these processes on porosity, permeability, flow localization, and pattern formation. Work at any scale is welcome; from single pores and table-top experiments to hydrogeological systems and sedimentary basins.

Per- and polyfluoroalkyl substances (PFAS) are persistent contaminants increasingly detected across terrestrial environments, from contaminated source zones and soils to the vadose zone, groundwater, and urban subsurface systems. PFAS persistence, mobility, complex sorption behaviour, precursor transformations, and interactions with air-water and soil-water interfaces in heterogeneous subsurface environments present challenges for understanding and predicting their long-term environmental fate. This session aims to bring together experimental, field-based, modelling, and remediation studies addressing PFAS as well as other emerging or traditional contaminants in terrestrial systems.
We welcome contributions that:
• Advance understanding of PFAS retention and mobilisation, source-zone behaviour, mass flux, transformation processes, and the performance and longevity of remediation technologies
• Explore the influence of hydroclimatic variability, including changing recharge, drought, snowmelt, and extreme precipitation.
• Map new contaminant pathways to soil and groundwater, including transport through urban subsurface environments and bedrock, where heterogeneous geological structures, preferential flow, infrastructure, and complex recharge conditions can influence contaminant migration.
• Investigate soil-bedrock-groundwater interactions and emerging approaches for identifying and quantifying these pathways
By connecting process understanding, field observations, modelling, and remediation, the session seeks to identify lessons learned, emerging challenges, and new pathways for predicting and managing persistent contamination in vadose zone and groundwater systems.

Topics include:
• PFAS/Contaminant fate and transport in vadose zone and groundwater systems, including surface water interactions
• Sorption, interfacial processes, precursor transformations, and PFAS mass flux
• Remediation technologies and long-term performance, including in-situ and on-site methods for stabilization, separation and destruction
• Hydroclimatic and hydrogeological controls on PFAS mobilization and groundwater contamination
• Model development and modelling studies
• Urban and bedrock transport pathways connecting contaminated terrestrial environments to groundwater
• Site characterization

Particles (inorganic particles, biocolloids, plastics) in environmental systems are of great concern because of their potential adverse effects on ecosystem functions, wildlife and human health. They may also alter the transport properties of dissolved contaminants and change the hydraulic properties of subsurface systems. On the other hand, engineered particles and biocolloids play an important role in site remediation and aquifer restoration. This interdisciplinary session fosters the exchange among scientists from hydrogeology, microbiology, ecotoxicology, engineering, and analytical chemistry in order to provide a general picture of the occurrence and fate of natural and engineered particles in aquatic and terrestrial systems.

We are expecting contributions in the following fields:
• occurrence, fate and transport of biocolloids, nanoparticles and other particles (microplastics, soot, ...) in aquatic and terrestrial systems
• methods to detect, characterize, and quantify particles in
aquatic and terrestrial systems
• advanced experimental methods to test the behaviour of particles in aquatic and terrestrial systems (mesocosms, non-invasive imaging, ...)
• interactions between biocolloids, particles and solid surfaces
• biocolloid biodegradation in the presence of solids
• toxicity of products generated from biological disruption of pollutants in the presence of biocolloids
• adverse effects of nanoparticles on microorganisms
• effects of climate change on biocolloid and nanoparticle migration
• public health risks associated with water and air polluted with biocolloids and nanoparticles.

This session focuses on the small-scale transport processes of plastic pollution (macro, micro- and nano-plastics) across aquatic environments and groundwaters. While we aim to place special emphasis on laboratory experiments and modelling approaches, we also welcome presentations employing field work, and contributions focused on theoretical concepts.

The presentations will revolve around understanding and characterising plastic movement and distribution, considering governing factors like particle physical characteristics, including size, shape, density, and surface chemistry, as well as environmental conditions such as flow, turbulence, temperature, salinity and suspended sediment. Relevant biological and chemical processes will be taken into account such as biofouling, aggregation and fragmentation, as well as plastic's role as transport vectors for other emerging contaminants, adding to their transport complexity.

Beyond the presentation of research findings, this session will also focus on advancements in laboratory and numerical techniques, highlighting improvements in accuracy, complexity, and spatial-temporal resolution. Cutting-edge modelling approaches tailored to simulate the transport dynamics of plastics in the environments will be showcased.
Through engaging discussions, the session aims to enhance our comprehension and predictive capabilities, while also identifying unresolved questions and paving the way for future research in this field.

Extreme hydroclimatic events are expected to increase in both frequency and intensity as a result of climate change. Groundwater systems are particularly vulnerable to these events, yet their medium- to long-term responses remain insufficiently understood. Consequences such as reduced aquifer recharge, sustained groundwater depletion, and groundwater quality degradation can induce cascading impacts including land subsidence, threats to freshwater availability and food security, and saltwater intrusion. It is therefore essential to advance our understanding of the full spectrum of these processes and their impacts, as well as to improve our ability to represent them through physics-based numerical modeling and machine learning approaches. Such knowledge can foster the implementation of effective mitigation and adaptation strategies to safeguard groundwater resources and ensure their sustainable use. These strategies can vary from improved forecasting and modeling of the impacts of extreme events on aquifer systems, to targeted engineering interventions and sustainable management practices.
This session invites contributions that provide insights into innovative methodologies, field case studies, or novel perspectives investigating the qualitative and quantitative impacts that extreme hydroclimatic events exert on groundwater systems, and their cascading environmental and socio-economic effects. In particular, we welcome studies that address: (i) evaluation of the combined effects of climatic extremes and anthropogenic stresses on groundwater quantity and quality; (ii) comparative analysis of field observations and methodologies unraveling system responses across different spatial scales and climatic contexts; (iii) development and application of physics-based, machine learning, or hybrid modeling frameworks for simulating past, present, and projected aquifer responses under extreme hydroclimatic events; (iv) characterization and modeling of system memory and recovery dynamics; (v) identification and evaluation of potential management, mitigation, and adaptation strategies to enhance groundwater resilience.

Groundwater provides about 40% of all human water abstractions and is an essential water source for terrestrial ecosystems and freshwater biota in rivers, lakes, and wetlands, as well as a keystone ecosystem in itself. Aquifers span political and natural boundaries, connecting people, ecosystems, and different parts of the hydrological cycle. However, our large-scale understanding of groundwater processes and the connection between ground and surface waters is still limited.
The development of global groundwater models and big-data assessments of groundwater monitoring data have helped to push the boundaries of our large-scale understanding of groundwater processes. In particular, knowledge of the exchange between surface and subsurface waters is essential for determining the water balance at larger scales. Surface and subsurface water exchanges and inter-catchment groundwater flow affect water, pollutant, and nutrient fluxes, bio-organisms in streams, and the groundwater itself. Additionally, human activities (e.g., pumping/irrigation) increasingly affect groundwater flow processes and the exchange between surface and subsurface waters.
In this session, we want to highlight the increasing interest in the large-scale study of groundwater availability, quality, and processes (including groundwater recharge) and discuss current obstacles related to data availability and model design. Therefore, we seek contributions that address issues including:
• Continental to global groundwater-related datasets
• Regional to global big-data assessments with models and machine learning
• Transboundary and inter-catchment assessments of groundwater processes
• Identification of dominant controls on groundwater processes across large domains
• Recent methodological developments for inclusion of small-scale hydrological processes into large-scale estimates
• Surface-subsurface water exchange and its effects on hydrological extremes (drought/flood), water availability, and solute and pollutant transport
• Effects of climate change, land use change, and water use change on global groundwater
• Implications of large-scale groundwater understanding on monitoring design, integrated water management, and global water policies
• Feedbacks between large-scale groundwater processes and groundwater users
• Large-scale groundwater assessments related to the fulfillment of the UN sustainable development goals (SDGs)

Groundwater resources face increasing pressures from climate change, abstraction, pollution and other human activities, requiring integrated approaches to assess groundwater quality and quantity and to support sustainable management. While monitoring provides the essential evidence base, heterogeneous monitoring networks, methods and assessment criteria still limit comparability and integration across Europe.
This session will explore how monitoring data, indicators, modelling and mapping tools can be harmonized and integrated to move from observations towards decision-making. A particular focus is on translating heterogeneous observations and scientific knowledge into robust, spatially explicit information that supports ground water management across scales, from water bodies to national and European assessments.
Contributions may address groundwater levels and storage, recharge and abstraction, natural baselines, trend assessments, anthropogenic pressures, uncertainty assessment, data harmonization, and the development of indicators and decision-support tools.
The session welcomes approaches supporting the implementation of the Water Framework Directive and Groundwater Directive, as well as broader European initiatives such as the EU Water Resilience Strategy and the Geological Service for Europe (GSEU).

Groundwater is one of the largest stores of freshwater on Earth. Yet, it remains one of the least directly observed components, with its dynamics often inferred from sparse observations, indirect measurements, models, and satellite and remote-sensing products. This limited observability contributes to persistent uncertainties in how groundwater interacts with other components of the hydrological cycle and regulates hydrological variability across spatial and temporal scales. Groundwater is not an isolated component. Through recharge, storage, subsurface flow, and exchanges with surface water and ecosystems, it can buffer or amplify hydrological variability, sustain river and ecosystem flows, influence drought propagation and recovery, and redistribute water across catchments and regions. Understanding these processes is essential for a complete picture of the water cycle under a changing climate. An emerging challenge is to move beyond viewing the terrestrial water cycle primarily as individual stores, fluxes and water-balance terms toward understanding its integrated connectivity and redistribution structure. Quantifying groundwater contributions and connectivity is important for understanding how the water cycle is organized, where uncertainty is concentrated, and how changes propagate through the wider hydrological system. We welcome contributions addressing, but not limited to:
• Groundwater dynamics and connectivity, including contributions to terrestrial water storage, streamflow, evapotranspiration, coastal discharge, and groundwater–surface-water interactions;
• Observing and quantifying groundwater using in situ measurements, remote sensing, geophysical and tracer-based methods, and integration of heterogeneous observations;
• Modelling groundwater within the hydrological cycle, including large-scale and Earth system models, precipitation/runoff partitioning, groundwater representation and uncertainties;
• AI-powered, data-driven and hybrid approaches, including data assimilation, machine learning, reconstruction, prediction and scaling;
• Groundwater roles in hydrological variability, change and extremes, including drought and flood onset, propagation, persistence and recovery, and responses to climate variability, climate change and human interventions; and
• Scaling and implications from local and catchment to continental and global hydrology, including ecosystems, water availability and resilience.

Sustainable groundwater management is becoming increasingly important as growing societal demands, environmental pressures, and climate change place unprecedented stress on water resources. Ensuring the long-term availability of groundwater requires an integrated approach that considers water quantity, water quality, ecosystem preservation, and society's needs. Effective management strategies must therefore account for both natural processes and human impacts, while enhancing the resilience of groundwater-dependent systems under changing climatic conditions.
This session aims to bring together case studies and scientific contributions addressing the sustainable management and protection of groundwater resources. Contributions are invited on topics including, but not limited to: (i) the application of environmental tracers, hydrochemical methods, and isotopic techniques to investigate groundwater processes and anthropogenic impacts; (ii) groundwater and hydrogeological budget assessments for evaluating water availability and sustainability; (iii) approaches for preventing, managing, and mitigating groundwater degradation caused by overexploitation, contamination, competing water demands, and climate change; and (iv) the identification of key challenges, emerging pressures, and innovative solutions for groundwater governance and protection; and (v) studies applying the concept of regional groundwater flow systems to improve the understanding, assessment, and sustainable management of groundwater resources and groundwater-dependent ecosystems. Contributions covering local, regional, and continental-scale studies are welcome.
The session is co-organized by the Regional Groundwater Flow Commission (RGFC) of the International Association of Hydrogeologists (IAH).

This session invites contributions that advance the understanding of groundwater in cold-climate hydrosystems. Groundwater in high-latitudes is controlled by prolonged cold winters, warm summers with intense vegetation growth, and precipitation distributed year-round. In these regions, atmospheric water is stored over winter as snowpack, soil frost commonly occurs, and permafrost may be absent, discontinuous, or temporary. Temperature plays a dominant role in cold-climate hydrogeological dynamics, making these systems particularly sensitive to global warming. In addition, these regions have recently experienced climate extremes, including unusually high temperatures and prolonged dry spells imposing new stresses. Land use and land cover are also climate-dependent, further exacerbating global change impacts. Across these regions, common hydrogeological patterns emerge: strong groundwater–surface water connectivity, widespread presence of wetlands, seasonality in groundwater recharge, short aquifer memory, typically low groundwater mineralization, and pronounced freeze–thaw impacts on infiltration and storage. Rapidly changing climate conditions are altering these dynamics, with implications for water resources, ecosystems, carbon and nutrient fluxes, and the resilience of communities and infrastructure.
Despite the widespread anthropogenic and ecosystem reliance on groundwater in cold-climates, there remains a gap in understanding how groundwater systems will evolve under climate change. In response, this session invites topics on the characterization of hydrogeological processes and their seasonal variability, cryohydrogeological mechanisms, northern groundwater vulnerability, ecosystem and biogeochemical linkages, droughts and floods, post-wildfire hydrogeological responses, and the quantification of environmental and climate-change impacts on cold-climate groundwater resources. We also welcome studies addressing groundwater management, adaptation measures, and interactions with ecosystems and society. The session will provide a platform to exchange ideas on field methodologies (including geophysics), challenges of long-term and year-round monitoring (in situ and remote), advances in data-driven and modeling approaches (including coupled hydro-climate models), and strategies for mitigating the impacts of global change. All scales of investigation are of interest, ranging from laboratory and field scale processes to regional and sub-continental systems.

The Critical Zone (CZ) encompasses natural and anthropogenic environments where air, water, soil and rock interact with ecosystems and society. Water connects these components through the transfer of matter and energy across a wide range of spatial and temporal scales. Although groundwater is a major reservoir within this integrated system, its role in linking surface and subsurface processes and in shaping the evolution of the CZ remains incompletely understood. The slow and heterogeneous dynamics of groundwater in particular make it challenging to identify how processes operating at different spatial and temporal scales interact and respond to environmental change.

This session welcomes contributions exploring groundwater processes and their interactions with other CZ components, from local to regional scales and from short-term dynamics to long-term evolution. We encourage observational, experimental and modelling studies, as well as approaches combining these perspectives, including data-driven methods and insights from long-term observatories. Contributions may address natural processes, interactions within ecosystems, or anthropogenic influences, including the effects of climate and land use change on groundwater and CZ dynamics.

Topics may include, but are not limited to: groundwater–surface water interactions and hyporheic processes; recharge, evapotranspiration and root-zone dynamics; groundwater-dependent ecosystems; weathering, solute and contaminant transport; mining-impacted and other human-modified systems; cold-region, coastal, karst and crystalline aquifers; and the use of tracers, isotopes and geophysics to constrain CZ processes.

By connecting processes, observations and models, this session aims to foster a more integrated understanding of groundwater within the CZ. We particularly welcome studies that bridge disciplines and scales, and we strongly encourage early-career researchers to submit their work.

This session focuses on the use of geophysical methods for characterising subsurface properties, states and processes in hydrology, hydrogeology, Critical Zone, contaminant transport, ecology and beyond. Topics of particular interest include groundwater flow and storage, aquifer and soil heterogeneity, soil moisture and vadose zone dynamics, transport processes and surface water–groundwater interactions, as well as the influence of subsurface heterogeneity on biogeochemical processes and microbial biodiversity.
Geophysical methods can provide subsurface information at exceptionally high spatial and temporal resolution in a non-invasive manner. However, the interpretation of these measurements remains far from straightforward in many applications and a number of challenges persist. These include improving the quantitative use of geophysical measurements for hydrogeological model conceptualisation and parameterisation, resolving structural and hydraulic heterogeneity and extending quantitative hydrogeophysical investigations beyond laboratory and field scales towards the catchment scale.
We therefore welcome submissions addressing advances in the acquisition, processing, analysis and interpretation of data obtained from geophysical and other minimally invasive methods applied to hydrogeological, hydrological, biogeochemical and contaminant-related problems. In particular, we encourage contributions on innovative experimental and numerical methods supporting model–data fusion, new concepts for coupled and joint inversion, and advances in petrophysical understanding of the relationships between geophysical properties and hydrogeological parameters, states and processes.

Information on groundwater residence times and flow paths can be used to understand the hydrological and biogeochemical functioning of aquifers including impacts of subsurface heterogeneities, seasonal and long-term changing climatic conditions, groundwater-surface water interactions and many other processes.
Tracer and model based estimates on residence times and flow paths are valuable tools to protect groundwater dependent ecosystems, to estimate vulnerabilities and recovery times of aquifers impacted by pollution, to define drinking water protection areas and for planning sustainable groundwater use.
The session wants to bring together experiences of applied resource management and advanced research using a wide range of different techniques including new tracers and advances in modelling techniques in variable aquifers at various spatial scales. Especially, welcome are presentations with new or not so frequently used tracers of long or short half-life.

Groundwater quantity and quality assessments traditionally rely on periodic observations, long-term trends, and threshold-based indicators. While these approaches underpin monitoring and regulatory assessment, emerging data and analytical capabilities raise a fundamental question: are we assessing groundwater through the wrong lens?
Groundwater observations can provide information not only on system status, but also on aquifer dynamics and functioning. Aquifers receive climatic and anthropogenic forcing and transform these signals through their hydrogeological properties, storage, connectivity, memory, and characteristic response times. Understanding these dynamics can reveal how groundwater systems respond to pressures, whether their behaviour is changing, and how they recover from disturbances—information that may remain hidden when assessment is limited to trends, averages, or threshold exceedances.
This session invites contributions exploring new ways to characterize and assess groundwater quantity and quality through the analysis of aquifer dynamics. We welcome studies using continuous and high-frequency records, multi-source observations, time-series analysis, dynamic indicators, response and recovery metrics, change detection, and other observational or analytical approaches. Particular interest is given to studies that characterize aquifer response, identify climatic and anthropogenic controls, detect changes in system behaviour, assess resilience, or translate dynamic information into meaningful indicators of groundwater condition.
The aim is to explore how a better understanding of aquifer dynamics can complement conventional groundwater assessment and support more diagnostic and anticipatory approaches to monitoring and management. Ultimately, the session asks: what can groundwater dynamics tell us about the condition and evolution of aquifers that snapshots, averages, trends, and thresholds cannot?

Groundwater recharge is a key component of the hydrological cycle and is essential for sustaining groundwater resources, ecosystems, agriculture, and water security. Climate change, land-use change, urbanization, and changing water-management practices are altering the magnitude, timing, and spatial distribution of recharge, creating new challenges for groundwater assessment and sustainable management.

This session brings together researchers to advance understanding of recharge processes under changing environmental and anthropogenic conditions. We welcome contributions on climate impacts, land-use and agricultural effects, natural and managed aquifer recharge, groundwater–surface water interactions, and recharge estimation using field observations, tracers, remote sensing, geophysics, and modelling. We also invite studies using data-driven and machine-learning approaches to quantify and predict recharge.

Contributions addressing uncertainty, scaling, emerging methodologies, and implications for groundwater sustainability and water security are particularly encouraged. The session aims to foster interdisciplinary discussion on how improved understanding and quantification of recharge can support resilient groundwater management in a changing world.

Coastal aquifers, pivotal freshwater reserves for millions worldwide, are increasingly vulnerable to seawater intrusion due to the joint impacts of climate change and intensive human activity. Rising sea levels, changing precipitation patterns, over-abstraction, land use change, and population growth intensify the stress on these valuable but fragile resources. As salinization threatens groundwater-dependent ecosystem health, agriculture, and urban water supplies, integrated approaches to monitoring, modelling, and managing coastal aquifers are urgently needed.

This session invites contributions that advance understanding, prediction, and management strategies for minimizing seawater intrusion and ensuring sustainable water resources in coastal regions. We aim to foster interdisciplinary discussion on innovative concepts, methods, and policies that support resilience under global-change scenarios.

We encourage submissions related to, but not limited to:

-Field and modelling studies of seawater-intrusion processes in coastal aquifers
-Impacts of climate change, including sea-level rise, extreme weather, and shifting recharge patterns, on groundwater salinization
-Effects of groundwater pumping, land-use change, and urbanization on aquifer vulnerability
-Advances in observation techniques, including hydrochemical and isotopic tracers, remote sensing, and geophysical methods
-Integrated management strategies and decision-support tools for sustainable groundwater extraction and adaptation
-Case stdies of coastal-aquifer restoration
-Nature-based solutions and managed aquifer recharge (MAR) to enhance coastal-aquifer resilience
-Socioeconomic, legal, and policy dimensions, including water quality, stakeholder involvement, and governance
-Multi-scale approaches, from local to global perspectives

Groundwater is a crucial source of water that underpins, supports, or sustains entire habitats and biocoenosis, ranging from wetlands, riparian zones, caves, aquifers, springs, forests, grasslands, and coastal environments. Conversely, ecosystem processes can significantly influence groundwater quality and dynamics. These interactions involve a diversity of ecological and hydrological processes such as groundwater uptake by vegetation, stream–aquifer exchange, biogeochemical reactions in aquifers, bioturbation by groundwater resident fauna, and soil–plant–atmosphere interactions. As these feedbacks are tightly connected to land surface, GDEs can be highly sensitive and vulnerable to anthropogenic pressures such as land use (change), water withdrawal, and climate change. Conversely, GDEs can provide important buffering capacities to environmental variability and extremes, and present important forms of Nature-based solutions. Further, GDEs often support human activities, from supporting pastoral livelihoods to underpinning cultural values. Thus, understanding groundwater-ecosystem interactions is not only important for the field of ecohydrogeology, but moreover to inform management policies and strategies that holistically integrate ecological, hydrological, and social outcomes. This session seeks contributions that: highlight the role of groundwater in sustaining ecosystems; examine the impacts and feedbacks linking diverse ecosystem processes with groundwater quality and quantity; the detection and delineation (i.e., mapping) of GDEs across local to global scales; and introduce of new methods to analyze interactions between groundwater and dependent ecosystems. Submissions that advance data acquisition methods; local-scale in-situ studies; empirical data analysis; ecohydrogeological model simulations; scaling of processes and their detection from the plant to regional scales; the resilience of GDEs and their connected systems; socioeconomic and cultural interactions and meanings of GDEs; and analytical developments are equally welcome. The session seeks to include work on GDEs across a wide range of physiographic and social contexts, including surface, unsaturated, and saturated zones; urban, rural, and coastal environments; and a wide range of socioeconomic and sociocultural contexts.

Data-driven modelling continues to gain momentum within the groundwater research community, reflecting strong interest in machine learning, AI and innovative approaches integrating data-driven techniques with physical process understanding. Data-driven approaches, including time-series models, statistical methods, machine and deep learning techniques and emulators, are transforming how we study, manage and forecast groundwater systems. By learning from observations and other sources, these methods can complement or even substitute detailed process-based models. Advancements in physics-informed methods, spatiotemporal deep learning, probabilistic machine learning, foundation-model approaches and generative AI are rapidly expanding possibilities for groundwater science.
We welcome novel methodological developments and practical applications addressing real-world groundwater management problems along the following topics:
Methodological Advances
-Modelling techniques and data-driven methods for predicting groundwater quantity/quality in space or time, such as machine learning, deep learning, statistical methods and time series models
-Hybrid approaches combining machine learning with conventional physical based models, including physics-informed neural networks
-Machine learning-based emulation of physical based models for enhanced modelling and data assimilation
-Applications of generative AI and large language models for synthetic data generation, knowledge extraction and model development for groundwater research and management workflows
Uncertainty and Interpretability
-Uncertainty quantification and sensitivity analysis using machine learning techniques, including probabilistic forecasting, quantile regression and deep ensembles
-Explainable and interpretable machine learning approaches to improve hydrogeological system understanding
Data Handling and Transferability
-Approaches for analysing big data and complex datasets from groundwater systems
- Solutions for data scarcity, multi-source/scale/fidelity data integration, non-stationary time series and irregular time steps
-Transferability and regionalization methods for spatial transfer to ungauged sites and temporal extrapolation to unseen conditions
In session you will engage with researchers working at the intersection of data science, process-based modelling and groundwater quantity/quality. Join us to share your research and advance this dynamic field through knowledge exchange and discussion.

Sustainable groundwater use depends on reliable estimates of groundwater recharge—a critical but difficult-to-quantify flux. Before water reaches the aquifer, surface inputs, vegetation, and vadose zone processes alter both its quantity and timing. Climate and land use changes, along with extreme events such as droughts and intense rainfall, further complicate the spatial and temporal dynamics of the recharge. Now more than ever, refining our understanding of recharge is critical to informing decisions and managing groundwater sustainably.
This session offers a platform to exchange concepts, expertise, and methods related to groundwater recharge estimation across disciplines and application contexts.
We invite contributions focusing on the estimation of groundwater recharge across multiple temporal and spatial scales, including studies that compare or combine different methods. Estimation approaches may be based on:
• Field-based measurements from various compartments of the hydrological cycle:
o Land surface water balance components
o Vadose zone measurements (e.g. soil moisture)
o Groundwater heads (water table fluctuations)
o Discharge measurements (baseflow separation)
o Environmental tracers for recharge estimation and model calibration (e.g., stable isotopes, radioisotopes, dissolved gases)
o Including suggestions for improved monitoring concepts
• Model-based approaches (local to global scale), such as:
o Water balance models
o Land surface models
o Physically-based vadose zone or groundwater models
o Hybrid or machine learning-supported methods
o Groundwater time-series models
• Upscaling strategies from point-scale to landscape-scale assessments
• Varying temporal scales from short-term recharge quantification to long-term recharge trends (past or future scenarios)
We welcome studies addressing recharge estimation for various purposes, including (but not limited to) agricultural water management and irrigation, forest management and ecosystem transition, groundwater resource planning, and sustainable management.

Emerging contaminants (e.g., PFAS, pharmaceuticals, microplastics) and climate change pose new challenges to our already fragile ecosystems. The vadose zone is a dynamically changing heterogeneous system, which plays a key role in regulating water and solute exchanges between atmosphere, vegetation, and groundwater and hosts a large portion of subsurface biochemical reactions. Understanding the interrelation between hydrological, physicochemical, and biological processes in the unsaturated zone is paramount to developing sustainable management strategies. This can solely be attained by translating novel experimental insights into well-validated modeling tools, which can benefit from recent advances in machine learning.
This session welcomes research that advances the current understanding of the vadose zone hydro-biogeochemical functioning across multiple scales, including experimental or modeling approaches, and field or simulation studies. In particular, we encourage researchers to participate with contributions on the following topics:
• Monitoring of water flow, solute transport, and biochemical reactions from the pore scale to the field scale
• Experimental investigation and numerical modeling of the reactive transport of emerging contaminants in variably-saturated porous media
• Influence of static and dynamically changing soil structures (e.g., heterogeneity) on water flow and reactive solute transport
• Transport of water and contaminants in/from the rhizosphere into the plant
• Development of novel modeling approaches to predict water and chemical transport in the vadose zone
• Novel techniques for model appraisal, including calibration, sensitivity analysis, uncertainty assessment, and surrogate-based modeling for hydro-biogeochemical vadose zone modeling.

Interactions between plants and their environment shape terrestrial fluxes, biochemical cycles, and agro-ecosystem productivity. However, we still lack detailed knowledge of how these interactions impact plant access to soil resources and, hence, plant growth, particularly under deficit conditions. The main challenge arises from the complexity inherent to biophysical and biochemical processes in soil and plants across multiple scales. To address these knowledge gaps, an improved understanding of soil-plant-related transfer processes is needed.

Quantitative approaches that integrate across disciplines and scales constitute stepping-stones to foster our understanding of fundamental biophysical processes at the interface between soil and plants. This session targets research investigating soil-plant-related resource transfer processes across different scales (from the rhizosphere to the global scale) and welcomes scientists from multiple disciplines encompassing soil and plant sciences across natural as well as agricultural systems. We are specifically inviting contributions on the following topics:

- Hot topics 2027: Heat and drought interactions, hybrid process-based and data-driven models
- Bridging the gap between biologically and physically oriented research in soil and plant sciences
- Measuring and modeling of soil-plant hydraulics and gas exchange, water, solute, and carbon fluxes through the soil-plant-atmosphere continuum across scales
- Identification of plant strategies to better access and use resources from the soil, including under abiotic stress(es)
- Experimental techniques such as non-invasive imaging and three-dimensional root system modeling tools
- Novel experimental and modeling techniques assessing belowground processes such as root growth, root water, and nutrient uptake, root exudation, microbial interactions, and soil aggregation
- Mechanistic understanding of plant water use and gas exchange regulation under drought and their implementation across scales (from cell to organ to single plant to agro- ecosystems, Earth system)

Observing soil moisture at the ground is essential to assess plant available water, manage water resources and calibrate, validate satellite products or environmental models 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 temporal availability 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 will address issues in the development and deployment of state-of-the-art soil moisture observation networks, the financing of their long-term operation, data quality assurance, data imputation, and data scaling 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 (primarily) in situ soil moisture to understand and assess hydrological processes, water availability, land-atmosphere feedbacks and soil moisture dependent hazards.

Blue and green water management is vital for sustainable and resilient food systems around the world.
This is true not only in drylands, where any productive activity is deeply related to the understanding of soil hydrological behaviour, and irrigation and green water management are key for agroecosystems’ health (e.g. being a defence against desertification), but in every socio-ecological ecosystem.
Also temperate or humid climates are, in fact, increasingly subjected to variations in the hydrological cycle, as well as to water scarcity and/or mis-management. Improper practices, which are not able to cope with climate-induced threats, may contribute to soil degradation and depletion of the available water resource. For example, incorrect irrigation techniques may lead to soil and groundwater salinization, with dramatic fallout on agricultural productivity.
Irrigation expansion, and paradoxically -through complex socio-hydrological dynamics- also irrigation efficiency improvements, could lead to increasing water consumption and water scarcity conditions . On the other hand, the role of irrigation goes beyond the technological aspects: traditional irrigation is a cultural heritage, which is often structurally resilient, and which needs to be faced with an interdisciplinary approach involving humanities.

This session welcomes contributions with a specific focus on:
- The understanding of the soil hydrological behaviour and of the mass fluxes through the soil in both drylands and environments under actual or projected water stress conditions (e.g. water shortage and/or mis-management, compaction, salinization)
- The understanding of the sociohydrological dynamics linking irrigation, green water, and soil management
- The interaction between irrigation, soil hydrology (including deep drainage) and socio-economic impacts.
- The analysis of the bio-geo-physical and social dynamics related to rainfed and irrigated agriculture in both arid and non-arid areas and oases, including rainwater harvesting, and managed aquifer recharge systems
- The management of rangeland areas, including their restoration
- The management and conservation of traditional irrigation systems, including the provision of co-benefits and ecosystem services

This session is co—sponsored by the International Commission on Irrigation and Drainage (ICID - https://icid-ciid.org/home); and by the International Center for Agriculture Research in the Dry Areas (ICARDA - https://icarda.org/).

The continuum approach is a classical framework to describe and understand the soil--water dynamics and the soil effective--stress state in unsaturated soils. This approach is robustly rooted in the definition of the soil--water constitutive laws (soil--water retention curve, soil hydraulic conductivity, Kirchhoff potential, etc.). They link the real soil and its model. Advancements along their development and the comprehension of their role stand at the intersection of experimental measurements, mathematical representation and modelling, numerical solutions, theoretical understandings and practical applications.

This session aims at stimulating an interdisciplinary discussion about the state of the art and recent advances about soil--water constitutive laws and soil physical and hydrological properties, in the framework of a continuum approach and contributing to define its limits.

Experimental, theoretical and numerical contributions are encouraged about, but not limited to, (1) scaling of soil--water constitutive laws and their changes in time and space as a consequence of seasonality, climatic changes, anthropogenic changes and pedogenesis; (2) physics of water--repellent soils, and of swelling, dispersive and collapsible soils; (3) constitutive laws for extremely dry conditions and for nearly saturated soils; (4) nonequilibrium and hysteretic behaviours; (5) limits of the Darcian approach in the presence of macroporosity; (6) heat transfer and dispersion; (7) freezing and thawing processes in permafrost; (8) mechanisms of incipient erosion; (9) mathematical functions of constitutive laws and their physical implications; (10) pedotransfer functions and database analysis.

Advancements along those lines will have major implications in many fields, ranging from hydrology, to soil science and soil physics, agriculture and geotechnics.

The transfer of sediments and associated contaminants plays an important role in catchment ecosystems as they directly influence water quality, habitat conditions, and biogeochemical cycles. Contaminants may include heavy metals, pesticides, nutrients, radionuclides, and various organic, as well as organometallic compounds. The environmental risk posed by sediment-bound contaminants is largely determined by the sources and rate at which sediments are delivered to surface water bodies, the residence time in catchments, lakes, and river systems, as well as biogeochemical transformation processes. However, the dynamics of sediment and contaminant redistribution is highly variable in space and time due to the complex non-linear processes involved. This session focuses on sources, transport pathways, storage, re-mobilization, and travel times of sediments and contaminants across temporal and spatial scales, as well as their impact on freshwater ecosystems.

This session particularly addresses the following key themes:
1) Sources and Pathways of Sediment and Contaminant Transfer
Understanding how sediments and contaminants originate from natural and human sources (e.g., agriculture, urban areas, mining, industry) and move through the land, river, lake, and reservoir continuum.
2) Transport Dynamics and Environmental Controls
Investigating the transport, retention, remobilization, and transformation of sediments and contaminants, including the influence of biogeochemical processes, human activities (such as hydropower and flood management), and changing environmental conditions.
3) Innovative and Cost-effective Monitoring and Modelling Methods
Developing and applying novel, low-cost, and open-source methods to quantify sediment and pollutant fluxes across different spatial and temporal scales.
4) Impacts on Ecosystems and Landscapes
Assessing how sediment and contaminant dynamics affect river systems, floodplains, riparian zones, in-stream ecosystems, landforms, and geomorphological processes.
5) Long-term Change and Human Influence:
Using sediment archives, sediment budgets, and catchment-scale analyses to evaluate historical trends and understand the effects of human activities and environmental change on sediment and contaminant dynamics over time.

Soil erosion is a key driver of land degradation, leading to a cascade of impacts from on-site soil loss and reduced agricultural yields to off-site consequences such as flooding and sediment and contaminant pollution of aquatic environments. The environmental, economic, and societal impacts of soil erosion require a comprehensive scientific understanding of the physical processes controlling soil detachment, transport, storage, and redistribution from hillslopes to catchments, lakes, and estuaries.
This cross-disciplinary session covers the latest scientific developments in soil erosion and sediment delivery. By integrating hydrology, geomorphology, soil sciences, and biogeosciences, we aim to unify all driving forces of land degradation and catchment particle-bound transport.
Our goal is to bridge the gap between plot-scale soil loss and catchment sediment routing, linking short-term monitoring with long-term observations. Advancing this process knowledge connects methodological developments to conceptual frameworks, promoting sustainable management.

The following topics will form the core areas of presentation and discussion:
• Measurements and Tracing: Field and lab experiments developing process understanding (e.g., interrill to gully erosion) and catchment sediment tracing techniques.
• Monitoring: Short- to long-term assessments tracking landscape changes via local field assessments, UAS, and broad-scale remote sensing.
• Modelling Approaches: Innovative simulation techniques, from empirical and process-based to data-driven, addressing runoff, gully erosion, sediment transport, and catchment sediment budgets from plot to global scales under current and future climate scenarios.
• Sediment and Contaminant Dynamics: Quantification of sediment transit or residence times, storage, remobilisation, and the biogeochemical controls of associated contaminant transport impacting riverine and lacustrine ecosystems.
• Mitigation, Restoration and Impacts: Evaluation of conservation strategies, including successes and failures in addressing the on-site and off-site impacts of land use change and disturbances (e.g., agriculture, forestry, mining, urbanisation, wildfires).
Ultimately, we explore conservation strategies that support stakeholders and global initiatives, including the EU Soil Monitoring Law, Land Degradation Neutrality by 2030, and the UN Decade on Ecosystem Restoration (2021-2030).

Quantitative information on the spatial patterns of soil redistribution during storms and on the sources supplying sediment to rivers is essential for advancing our understanding of the processes that control sediment transfer and for designing effective management strategies. It is also crucial to quantify sediment residence times and to reconstruct changes in sediment sources across a range of temporal scales. These needs are becoming increasingly urgent in light of intensified climate- and land use-driven impacts on erosion, sediment delivery, and sediment-related pollution affecting freshwater and marine environments. Over recent decades, sediment tracing (or fingerprinting) techniques, used alone or in combination with other approaches (including soil erosion modelling and sediment budgeting), have provided valuable insights to understand sediment source dynamics. Yet, their widespread application remains constrained by several methodological and conceptual challenges that the research community should address. We welcome contributions that address any of the following aspects:
• Developments of innovative field measurement and sediment sampling techniques;
• Advances in the accuracy and robustness of soil and sediment tracing techniques for quantifying soil erosion and redistribution;
• Sediment source tracing studies using conventional (e.g. elemental/isotopic geochemistry, fallout radionuclides, organic matter) or alternative (e.g. colour, infrared, hyperspectral, particle morphometry, eDNA) properties including methodological developments;
• Investigation of particle-bound contaminant transfers in catchments and river systems using sediment tracing techniques;
• Investigations of the current limitations in sediment tracing studies (e.g. tracer selection, tracer conservativeness, uncertainty analysis, particle size and organic matter corrections);
• Applications of radioisotope tracers to quantify sediment transit times over a broad range of timescales (from the flood to the century);
• Association of conventional techniques with remote sensing and emerging technologies (e.g. LiDAR, satellite);
• Cross-regional and multi-scale applications of tracing techniques to establish generic characterisations of source contributions;
• Integrated approaches to developing catchment sediment budgets: combining different measurement techniques, monitoring, and/or models to improve our understanding of sediment delivery processes.

Human activities have profoundly altered Earth-surface processes and ecosystems during the Anthropocene, modifying erosion and sediment dynamics, biogeochemical cycles, biodiversity, and ecosystem functioning. At the same time, these anthropogenic pressures interact with hydroclimatic variability and extreme events, potentially amplifying their impacts and resulting in compound effects.

Recent sedimentary records from lakes, wetlands, reservoirs and fluvial systems provide high-resolution archives for reconstructing human–climate–environment interactions over timescales ranging from decades to centuries. By integrating environmental responses across spatial and temporal scales, these archives can document the timing, magnitude and persistence of disturbances, identify their sources and pathways, and reveal long-term trajectories, legacy effects, thresholds, and patterns of ecosystem resilience and recovery.

In this session, we invite contributions using recent sedimentary archives to reconstruct environmental changes and trajectories during the Anthropocene. We particularly welcome studies addressing land-use and land-cover changes and their impacts on erosion, sediment sources and connectivity; contaminant inputs and their fate (e.g. metals, organic contaminants, radionuclides and microplastics); changes in biodiversity and ecosystem functioning; and interactions between anthropogenic pressures, hydroclimatic variability and extreme events. Studies investigating pollution legacies, ecosystem recovery, and sedimentary responses to restoration and catchment-management practices are also encouraged. Methodological contributions using or developing innovative proxies (e.g. sedDNA, CSSI and isotopic approaches), dating methods, sediment-source tracing and multidisciplinary analyses of recent sediment records are also encouraged.

Rapid environmental change and increasing pressures on land and water systems highlight the need to better understand sediment dynamics across river basins. This session brings together research spanning the source-to-sink continuum, from soil erosion and sediment generation on hillslopes and uplands to sediment transport, connectivity, deposition, river processes, and reservoir sedimentation.
We welcome contributions that advance understanding through experiments, observations, monitoring, remote sensing, modelling, and data-driven approaches, including sediment tracing and fingerprinting. We particularly encourage studies addressing sediment dynamics under climate and land-use change, including extreme sediment-mobilizing events such as sediment-laden floods, debris flows, landslide-generated sediment pulses, and their downstream consequences.
Contributions addressing river and catchment management, reservoir sedimentation, restoration, nature-based solutions, and sustainable sediment management are also encouraged. The session aims to connect fundamental process understanding with practical applications and foster interaction among researchers working across hydrology, geomorphology, sediment transport, environmental engineering, and related disciplines. We particularly welcome contributions from early-career researchers alongside established scientists and practitioners.

This session brings together scientists, scholars, and engineers researching, teaching, and applying innovative measurement and monitoring techniques to analyze sedimentary, hydro-morphological, and hydraulic/hydrodynamic processes in open water environments such as rivers, lakes, reservoirs, estuaries, and coasts. The focus is on evaluating sediment transport phenomena—bed load, suspended load, bedform and channel migration, bed armoring, and colmation—along with modes of transport, flocculation, settling, and re-suspension. Integration of hydraulic and hydrodynamic measurements supports a comprehensive understanding of flow and morphodynamic interactions.
The session also promotes integrating nature-based solutions to enhance sediment management, reduce erosion, and improve ecosystem resilience. Contributions are invited on single and combined measurement techniques, post-processing methods, innovative monitoring approaches, and applications in both field and laboratory settings. Insights on sediment budgets, hydraulic and hydrodynamic analyses, and sedimentary and morphodynamic processes across temporal and spatial scales are welcome.
Topics include:
- Suspended and bed load sediment transport measurements with optical, acoustic, sampling, tracer, or other techniques.
- Hydraulic and hydrodynamic measurements (velocity, turbulence, resistance, energy dissipation).
- Sediment characterization using samplers or freeze-core methods.
- Innovative approaches for validating and calibrating numerical and hydrodynamic models.
- Critical bed shear stress measurements of cohesive sediments.
- Monitoring morphological changes: sedimentation, erosion, armoring, meandering.
- Measurement networks, multi-point datasets, and large or small-scale monitoring concepts.
- In-situ or lab calibration, including machine learning approaches.
- Applications of nature-based solutions, such as wetland restoration, riparian buffers, and living shorelines.

Hydro-morphological processes, encompassing sediment erosion, transport, and deposition, play a critical role in shaping open water environments such as rivers, lakes, reservoirs, estuaries, and coastal regions. Understanding and predicting these processes are vital for both scientific research and practical applications. In recent decades, numerical modeling has become an indispensable tool in hydraulic engineering and geosciences for simulating the complex interactions between flow, sediment, and environmental dynamics. Advances in algorithms and computational power now allow for high-resolution hydrodynamic simulations, supporting studies that explore water motion, sediment behavior, and their combined influence on morphology. Increasing availability of high-quality lab and field validation data continues to enhance these models, leading to deeper insights into phenomena like bed evolution, dune dynamics, and density-driven flows. Artificial Intelligence (AI) is also emerging as a complementary approach for hydro-morphodynamic analysis.
This session aims to bring together scientists and engineers who develop, improve, or apply hydrodynamic and hydro-morphodynamic models for open water environments. We welcome contributions that address a spectrum of spatiotemporal scales, from localized flow structures influencing sediment mobilization to basin-scale morphological evolution and hydrodynamic behavior. Both process-based simulations and data-driven methods are encouraged, particularly where they enhance our understanding of flow–morphology interactions and support nature-based solutions for water and sediment management. Contributions may include, but are not limited to:
- Hydrodynamic modeling of open water systems, including unsteady and density-driven flows.
- Flow–sediment interactions, from initial particle entrainment to morphological change.
- Simulations supporting river, lake, and reservoir management with an emphasis on nature-based solutions.
- Design and assessment of river and estuarine restoration measures integrating nature-based solutions.
- Navigation and infrastructure issues, including hydrodynamic effects of ship traffic.
- Flood-related risks and the role of hydrodynamics in long-term bed evolution.
- Eco-hydrodynamics, focusing on interactions among flow, sediment, vegetation, and nature-based strategies.

River basins worldwide are increasingly confronted by a twin challenge whereby excess sediment from accelerated erosion threatens water quality, aquatic ecosystems, infrastructure and reservoir capacity (too much), whilst sediment deficits downstream compromise river, delta and coastal resilience (too little). These challenges are being amplified by climate change, land-use change, infrastructure development, pollution, resource extraction and increasing pressures on food, water and energy security. While advances in sediment science have greatly improved knowledge, significant challenges remain in translating evidence into effective policies, governance frameworks and management actions.

This session aims to advance dialogue on how scientific understanding of river basin sediment dynamics, and associated contaminants, can better support governance and decision making across the source-to-sink continuum. It interconnects with the International Sediment Initiative (ISI), a flagship initiative of the UNESCO Intergovernmental Hydrological Programme (IHP), which was established to strengthen the links between sediment science, policy and management and to promote sustainable sediment management at local, regional and global scales.

Focusing on the science-policy-practice interface for erosion & sedimentation within river basin and channel processes, we invite contributions that demonstrate how sediment science is supporting policy development, environmental regulation, river basin management, disaster risk reduction, climate adaptation and ecosystem restoration at local, national and international scales. We welcome contributions that move beyond process understanding and methodological development to examine the uptake, application and impact of sediment knowledge in decision-making contexts.

Relevant to researchers, practitioners, policymakers and international organisations, the session will provide a forum to share experiences, lessons learned and emerging approaches for translating sediment science into policy and practice, with the aim of strengthening sustainable sediment management across local to global scales.

Ecohydrology, i.e., the study of the interactions between water and ecosystems, has expanded rapidly as a field of research, beyond traditional discipline boundaries in terms of questions and approaches. This session aims to draw examples from this wide field, portraying the current diversity and common features of research frontiers in ecohydrological studies, as well as the range of methods employed. We thus encourage contributions showing novel results or methods when tackling questions related to the coupling of ecological, biogeochemical and hydrological processes, at scales ranging from the single organ or organisms to whole ecosystem/catchment. Contributions relative to all terrestrial and aquatic systems are welcome, including those relative to managed ecosystems, showing how human intervention alters the interactions between water and ecosystems.

Plant hydraulics, which studies the capacity of plants to extract water from the soil and transport it up to the aerial organs, and ecohydrology, which studies the bidirectional interaction between the water cycle and ecosystems, share substantial conceptual overlap. Yet, communication between the two research communities remains limited.
This session aims to bridge this gap by soliciting contributions that present case studies that have benefited, or could benefit, from an interdisciplinary approach. Relevant topics include, but are not limited to:
• Ecohydrological processes in complex landscapes, including ecological studies at sites with significant lateral water fluxes, groundwater-dependent ecosystems, and landscape evolution contexts
• Vegetation-water interactions under environmental change, encompassing drought studies and forest hydrological research in both urban and natural catchments
• Plant hydraulic traits and ecosystem functioning, focusing on the ecohydrological implications of plant hydraulic strategies across scales
• Linking plant and catchment water dynamics through observations and modelling, including the use of isotopes and other novel measurement techniques, scaling approaches and integration of plant hydraulics into ecohydrological models
To facilitate meaningful exchange between the communities, contributors are encouraged to explicitly highlight the realised or anticipated benefits of integrating concepts, methods, or perspectives from the complementary discipline, for example through advances in theory, improved interpretation of observations, or the development of modelling approaches.

Forest ecosystems interact strongly with hydrological processes across a wide range of spatial and temporal scales. Their interactions with soils, groundwater and topography, together with often extensive root systems, create complex pathways for water movement through forest ecosystems. These include the interception, storage and redistribution of water in forest canopies before it reaches the soil, the infiltration and redistribution of water in the soil and subsurface, interactions with groundwater, and the uptake of water by roots and its subsequent transport to the atmosphere. Understanding these often-hidden connections is essential for quantifying forest water use and the role of forests in the water cycle.

Our ability to detect these processes is expanding through new approaches, including geochemical and isotopic tracers, geophysical and remote sensing techniques, high-resolution measurements and process-based modelling. These approaches provide new and sometimes surprising perspectives on water fluxes in forested ecosystems. The exceptional drought and heat experienced across large parts of Europe in 2026 further highlight the importance of understanding how forests access, redistribute and use water.

This session welcomes contributions that provide new insights into forest ecohydrological processes or demonstrate novel approaches to observing and modelling water fluxes in forest ecosystems. We particularly invite studies addressing how forest canopies modify water availability and fluxes, including interception, throughfall and stemflow; water movement through the soil and subsurface; root water uptake and water sources; and the transport and use of water within trees, as well as forest water stress, drought responses, and the links between forest hydrological processes and the water, carbon and nutrient cycles.

Hydrology and soil science originated from water-management needs for ancient civilisation and agriculture, but since then have developed into many specialised disciplines. While irrigation and yield management remain prominent research topics, agricultural fields as soil-plant-atmosphere systems are rarely seen as an integrated hydrological system, despite the pressing challenges posed by intensifying climatic extremes, degrading soils and declining water resources.
This session therefore refocuses attention on agricultural fields as coupled soil-plant-atmosphere systems in which hydrological, biogeochemical and ecological processes interact. Interdisciplinary approaches are crucial to improve process understanding for enhancing agricultural practices and making agricultural landscapes more resilient.
Given the contrasting temporal and spatial legacies of the processes involved, we need to consider agricultural landscapes under change. How can we prospectively manage systems with different process turnover scales? Moreover, which system-stabilising processes exist to make the landscapes more resilient, not only through “isolated” measures such as retention basins or hedges, but by enhancing characteristics and properties across entire fields or landscapes (e.g. improving soil structure to increase infiltration capacities)?

We invite contributions investigating soil-plant-atmosphere interactions, water, carbon and nutrient cycling, crop responses to environmental stress, and other processes shaping agricultural landscapes across temporal and spatial scales.
We particularly encourage contributions addressing how fundamental process understanding can inform agricultural management practices and modelling approaches. It is important to us to strengthen the connection between different scales – for example, linking small-scale and/or short-term observations and large-scale and/or long-term system responses, and translating them into management strategies/practices and applications.

This session aims to foster exchange between fundamental and applied research, and discussion about transforming interdisciplinary collaboration to impactful solution prospects.

How do soil-plant-atmosphere interactions shape hydrological and vegetation responses to climate extremes? How do antecedent soil-water and vegetation conditions influence the pathways through which droughts, heatwaves and floods affect agricultural and natural systems? Which approaches can explain contrasting responses and improve predictions?
This session explores soil-plant-atmosphere processes and hydrological pathways during the onset and development of climate extremes and subsequent recovery. We examine links between meteorological forcing, antecedent system states, plant water use, land-atmosphere exchanges and hydrological responses, from field to catchment scales. We welcome studies of contrasting responses under dry and wet conditions, drought-heat interactions and transitions between extremes.
Topics of interest:
1. Soil-plant-atmosphere responses and feedbacks. Root water uptake, plant water regulation, evapotranspiration, canopy energy balance and vegetation stress during droughts, heatwaves and excess water, including soil-water supply and atmospheric demand interactions.
2. Antecedent conditions and hydrological pathways. How soil moisture, root-zone water storage, vegetation condition and groundwater connectivity shape responses to extremes; how water storage and partitioning among evapotranspiration, drainage, recharge and runoff link plant water availability to broader hydrological behaviour.
3. Contrasting extremes, event sequences and recovery. Contrasting responses under different initial conditions; drought-to-flood transitions; compound hot-dry conditions; and hydrological and vegetation recovery: timing, thresholds and legacy effects.
4. Observation-informed process understanding and prediction. Combining observations and models to identify response pathways, test process explanations, link spatial scales and assess predictive performance across events and environmental conditions.
We welcome research using satellite and uncrewed aircraft system (UAS) remote sensing, field experiments, process-based models, data assimilation and interpretable or hybrid machine learning, especially integrating soil-water, vegetation, surface-flux and hydrological observations.
Studies may examine single extremes or processes or compare events and systems. We link soil-plant-atmosphere and hydrological extremes research to explain how initial conditions and interacting processes shape responses and recovery.

Evapotranspiration (ET) is the key water flux at the interface of soil, vegetation and atmosphere. Methods to derive this flux or its individual components from in-situ measurements have been developed in various research disciplines, covering different scales from e.g. point scale sap flow or soil heat pulse measurements, via pedon-scale of lysimeters, ecosystem scale of eddy covariance footprints to the landscape scale via drones or scintillometers. In-situ-measurements are necessary for calibration, validation and comparisons with larger scale estimates from remote sensing and modelling, but scaling procedures and uncertainty estimations are required for meaningful comparisons. Additionally, the support of these processes by AI methods holds much promise, but usually depends on large well-described data sets.

This session will mainly focus on the variety of in-situ ET estimates such as from sap flow or soil heat pulse sensors, lysimeters, eddy covariance stations, scintillometers and other (possibly new) methods. We would also like to address the challenges in comparing the different in-situ estimates while dealing with scale-dependency, uncertainty and representativity. We welcome contributions that (1) assess and compare established and new in-situ measurements, (2) address error sources and uncertainty considerations of the respective methods, (3) bridge scales between different in-situ measurements and modelled and remotely sensed ET, (4) demonstrate the value of in situ ET measurements to improve modelling of ET or characterizing large scale ET in combination with remote sensing; (5) evaluate challenges and opportunities of using AI for in-situ scaling and comparisons.

Stable isotopes are powerful tools for tracing water fluxes and associated nutrients in the soil-plant-atmosphere continuum. Because subsurface water and nutrient fluxes, plant water uptake, and atmospheric processes are tightly interconnected, advances in field methods, laboratory techniques, and modeling are critical for capturing these dynamics and their drivers with greater temporal and spatial resolution, precision, and accuracy. At the same time, ecohydrological models are expanding our ability to integrate these observations and assess fluxes in the soil-plant-atmosphere continuum. This session welcomes experimental and modeling contributions that apply isotope tracers to advance process-based understanding of water and nutrient fluxes across the subsurface, vegetation, and atmosphere, spanning scales from individual plants and forest stands to catchments. In our session, we aim to discuss i) innovative process-based interpretations of stable isotope data; ii) bridge ecophysiological and hydrological perspectives through field-based approaches; iii) development of novel modeling applications and frameworks or data analysis techniques; and iv) current methodological developments. We aim to foster interdisciplinary exchange among researchers investigating ecohydrological processes with natural tracers, spanning groundwater and vadose zone hydrology, plant physiology, and ecology. By linking subsurface hydrology with ecophysiological process studies, the session will showcase cutting-edge methodological advances and stimulate discussion to deepen our understanding of water and nutrient dynamics across the soil–plant–atmosphere continuum.

This session invites contributions that advance the observation, understanding, and modelling of ecohydrological processes across spatial and temporal scales. We particularly welcome studies of vegetation–water interactions, including root water uptake, evaporation and transpiration, canopy interception, soil moisture–plant feedbacks, and ecosystem responses to climatic and environmental changes. Contributions combining experiments, in-situ observations, remote sensing, data-driven approaches, and process-based modelling are encouraged, with particular emphasis on identifying mechanisms, understanding their variability across scales, and improving the representation and prediction of ecohydrological processes.

A particular focus is placed on scaling, data-model integration, and transferability: how can observations and process understanding obtained at fine spatial and temporal scales be translated into reliable predictions across heterogeneous landscapes and under climatic, ecological, and land-use change? Contributions addressing model evaluation, uncertainty, parameterization, scaling, and transferability across contrasting environments are especially encouraged. We also welcome work that connects improved predictive capability to challenges in ecosystem, water resources, and land management.

Topics of interest include, but are not limited to: (1) ecohydrological mechanisms and feedbacks among hydrological, ecological, and biogeochemical processes; (2) multi-scale observation and modelling of ecohydrological processes; and (3) scaling, model evaluation, uncertainty, and transferability across heterogeneous landscapes and changing climatic, ecological, and land-use conditions.

The session aims to bring together approaches that advance fundamental process understanding and the predictive capability of ecohydrological models, fostering new perspectives on how ecohydrological knowledge can be translated across scales and environmental conditions.

Hydrological extremes, water abstraction and reservoir operations are driving many lakes and reservoirs through low water, fragmented, dry and reflooded states. These transitions alter more than surface area and storage: they change residence time and connectivity, expose sediments to oxidation and desiccation, and reorganize exchanges among catchments, sediments, water and the atmosphere. Their sequence and duration can therefore generate thresholds, delayed recovery and persistent legacies in water quality and ecosystem function.
During contraction, solutes and contaminants may concentrate while littoral and bottom sediments become exposed. Drying changes redox conditions, microbial activity and organic matter processing. Reflooding can remobilize nutrients, salts, metals, suspended sediment and organic contaminants, trigger oxygen demand and greenhouse gas pulses, and reshape habitats and food web interactions. In managed reservoirs, the timing and rate of drawdown and refilling may amplify or reduce these effects.
The session will bring together hydrology, limnology, aquatic biogeochemistry, water quality, ecology, Earth observation and reservoir management. We invite field and experimental studies, in situ observations, water and sediment analyses, remote sensing, process based and data driven modelling, and regional or global assessments. Relevant topics include detection and attribution of state transitions; thresholds, hysteresis and recovery; sediment exposure and rewetting; carbon, nutrient and contaminant dynamics; ecological resistance and resilience; and monitoring, restoration and adaptive reservoir operation. By treating contraction, drying and reflooding as a connected trajectory, the session will examine when responses are reversible, when legacies persist, and how observations and management can reduce risks to water quality and ecosystem function.

Held regularly since 2005, the session has established itself at the EGU as the primary platform for advancing limnology within the geophysical community. As confined water bodies, lakes and inland seas are particularly vulnerable to climatic and human impacts accumulated over broad catchment areas. Hence, they mirror both the global change effects and anthropogenic pressures stronger than any other aquatic objects. Research of lakes and inland seas admits many common approaches and techniques. Oceanographic methodology and instrumentation are often applicable to limnological studies. Reciprocally, insights obtained from lakes can also be instructive with respect to marine systems. Lakes and inland seas also play an important role in ecosystem services such as fisheries, aquaculture, tourism. These multifunctional roles require careful governance measures to avoid hydrological and environmental deterioration. The session brings together specialists in limnology, hydrology, boundary-layer meteorology, and oceanography of inland seas to discuss the role of lakes in the land-atmosphere interaction, the response of lakes and inland seas to global change, the physical and biogeochemical interactions within the enclosed aquatic systems. The session offers an interdisciplinary forum for discussing novel advances in observational, modeling and remote sensing studies on lakes.

Wetlands and their associated wetlandscapes are strongly controlled by hydrological processes that determine water availability, connectivity, inundation patterns, and other key dynamics. These processes in turn are recently driven by climate change and human pressures, affecting ecosystem services such as water quantity and quality regulation, carbon storage, and food provision. Linking changes in water availability with pressures and services can therefore provide a stronger basis for wetland management, restoration, protection and conservation.
This session aims to address the following question: How do climatic and human pressures alter hydrological, geomorphological and ecological processes in inland and coastal wetlands and wetlandscapes, and what are the consequences for communities and society?
We welcome studies using remote sensing, hydrogeodesy, hydrological modelling and field observations to understand water-related changes in both water quality and quantity (represented by water surface area, depth, connectivity and storage). The processes seeking to be understood include hydroperiod, inundation dynamics, carbon and nutrient cycling, pollution, socio-hydrological interactions and how changes in ecosystem condition influence ecosystem services and livelihoods.
Contributions that combine multiple data sources or connect understanding of wetland processes with management and decision-making are also encouraged.

Integrating hydrological, biogeochemical, and ecological perspectives is essential to understand spatial and temporal dynamics of biogeochemical processes and ecosystem functioning in freshwater, and their emergent responses and sensitivity to a rapidly changing climate. Hydrological processes shape terrestrial-aquatic connectivity within catchments, with cascading effects on aquatic ecosystems through the mobilization and transport of chemical elements and organic compounds, as well as the dispersal of organisms. On the other hand, biota influences hydrological processes through mechanisms such as tree transpiration and ecosystem engineering, while regulating the biogeochemical cycling of carbon, nutrients, metals, and pollutants.

This session aims to advance understanding of these multifaceted processes by integrating perspectives at the terrestrial-aquatic-atmospheric interface. We welcome contributions that integrate hydrology, biogeochemistry, and ecology across different organizational and spatial scales, from organisms and communities to stream reaches, lakes, river networks, and catchments. Relevant topics include carbon and nutrient cycling and associated fluxes in soils and inland waters, ecohydrological dynamics, riverine metacommunities, food webs, greenhouse gas exchange, and ecosystem responses to anthropogenic and environmental pressures, including land-use and climate change.

We particularly encourage submissions that develop or combine innovative methods, including remote sensing, machine learning, mathematical modeling, and novel laboratory or field approaches, to address current spatial and temporal data limitations. We also welcome studies that apply concepts, tools, or methods from one discipline to generate new insights in another. By bringing together scientists from diverse backgrounds, this session seeks to foster interdisciplinary dialogue, promote methodological exchange, and stimulate new collaborations in hydrological, biogeochemical, and ecological research.

Lakes are sentinels of climate change and human pressure, yet harmful algal blooms, loss of aquatic vegetation and water-quality deterioration are intensifying worldwide. Recent progress in satellite and UAV remote sensing, high-frequency sensor networks and artificial intelligence opens new opportunities for "smart" lake monitoring and operational early warning. This session invites contributions on: (1) retrieval algorithms for water-quality parameters (chlorophyll-a, cyanobacteria, turbidity, CDOM) and aquatic vegetation from multi-source remote sensing; (2) integration of in-situ, optical and physiological measurements for calibration and validation; (3) long-term (multi-decadal) reconstruction of lake ecosystem change; (4) data-driven and hybrid models (e.g. deep learning, KAN) for short-term forecasting of bloom events; and (5) cloud platforms (e.g. Google Earth Engine), open tools and management applications. We particularly welcome comparative studies across lakes and regions, as well as contributions from early-career scientists.

Environmental DNA (eDNA) has become a popular biological survey tool, but its potential as a tracer of water and sediment transport remains underexplored. Understanding how eDNA signals are generated, mobilized, degraded, and preserved in water is essential not only for tracking biodiversity, but might reveal flow paths, residence time, sediment origin, and connectivity across hydrological and geophysical systems. This session is dedicated to exploring eDNA as a tracer of transport, discussing it alongside the established toolkit of hydrological tracers, including stable water isotopes, hydrochemistry, and particles such as fluorescent microspheres, bacteriophages, and spores. Recent work has demonstrated the feasibility of using eDNA to characterize flow paths and catchment response in Alpine and urban systems, and of incorporating eDNA sampling directly into hydrological monitoring and time series studies. Our primary focus is on recent-time eDNA signals in freshwater and surface waters, but we also welcome contributions that link present-day eDNA patterns to longer-term records preserved in sediment archives. Beyond rivers, we are interested in studies from wetlands, groundwater, and even lakes, coastal waters, and oceans.

Presentations in this session will address the methodologies, applications, and implications of eDNA for understanding the movement, persistence, and transformation of genetic tracer material within hydrological and geophysical systems. We encourage contributions that investigate how eDNA distribution is shaped by transport mechanisms, degradation kinetics, and environmental drivers such as flow, sediment, and biogeochemistry and what that knowledge can reveal about the underlying physical processes. Studies that integrate laboratory analyses, modeling, or sediment archives to connect scales and processes are particularly welcome. We also seek contributions that push the boundaries of how eDNA is observed. This includes innovative sampling strategies such as custom-built sensors and passive samplers, automated or distributed collection networks, and citizen science approaches that expand the spatial and temporal characterization of eDNA signal transport, concentration, and decay. By bringing together diverse systems and approaches, this session aims to advance eDNA as a tool for tracing physical transport processes, fostering new interdisciplinary collaborations between hydrology, sedimentology, and molecular methods.

Catchments are spatially heterogeneous because of topography, soils, vegetation covers, and climate. These features shape the redistribution of water, energy, carbon, and nutrients in the landscape, influence hydrological connectivity, and create biogeochemical hotspots. This session explores how the spatial organization of landscapes, soil, and vegetation cover shapes coupled water, energy, carbon, and nutrient processes in heterogenous landscapes. We welcome observational, experimental, process-based modelling, and AI/ML-driven studies that identify the mechanisms organizing the spatial patterns of ecohydrological processes and feedbacks. Relevant topics include simulated and observed spatial patterns of water, carbon, and water quality and underlying mechanisms; hydrological connectivity and lateral transfers; the emergence of biogeochemical hotspots; propagation of local dynamics to catchment-scale carbon, nutrient, sediment, and pollution export; and spatially heterogeneous responses to climate change. We also encourage cross-catchments studies that compare contrasting landscapes, explicitly consider spatial heterogeneity, and larger-scale study that develop approaches for representing sub-catchment and sub-grid heterogeneity at regional and continental scales. This session potentially brings together hydrologists, biogeochemists, and modelers that improved the process understanding and modelling ability of coupled water, energy and elements in spatially heterogeneous catchments.

Peatland hydrology is a key control on peatland vegetation, carbon cycling and greenhouse gas exchange. Peatland hydrology can change substantially following drainage, restoration, permafrost thaw and other disturbances, as well as in response to changes in precipitation and evapotranspiration. These changes affect not only water-table depth but also peat hydraulic properties, groundwater and surface-water exchange, runoff and hydrological connectivity.

This session brings together studies of hydrological processes in peatlands across tropical, temperate, boreal and subarctic regions. Studies from tropical, permafrost and other regions where peatland hydrology remains poorly observed are particularly encouraged, as are studies evaluating hydrological responses to disturbance, climate change and restoration.

We welcome contributions from pristine, drained, degraded, managed and restored peatlands. Topics may include:

- water-table dynamics,
- peat hydraulic properties,
- groundwater–surface water interactions,
- aquifer–peatland connectivity,
- evapotranspiration,
- runoff and streamflow,
- as well as interactions between hydrology, vegetation, biogeochemistry and greenhouse gas exchange.

We particularly welcome studies that consider hydrological processes below the near-surface peat layer and interactions between peatlands and the surrounding groundwater and surface-water systems.

We invite field and laboratory studies, long-term observations, remote sensing, geophysical methods and modelling approaches across scales from pore and individual peat profiles to catchments and continental regions.

Dynamic bidirectional exchanges between groundwater and surface water systems give rise to critical transition zones - including the hyporheic zone, the benthic layer, riparian corridors, wetlands, and lake sediments - where unique hydrological, biogeochemical, and ecological processes converge. These transition zones regulate the transport and transformation of nutrients, microplastics, and pollutants across hydrological copartments and associated aquatic ecosystems. They also control the availability of heat, oxygen, and organic matter within sediments, shaping habitat conditions for microorganisms and macroinvertebrates. Despite intese research, further investigation is needed to establish a comprehensive understanding of the physical, biogeochemical, and ecological processes occurring at groundwater-surface water interfaces, and their implications for fluvial ecology and limnology. Furthermore, it is essential to consider how exchange fluxes respond to environmental and climate factors associated with different spatial and temporal scales, spanning the sediment layer, river channel, alluvial aquifer, and regional groundwater scales. Upscaling and downscaling of a general conceptual framework, as well as enhancing process comprehension, are identified as the most significant challenges in this field of research. We invite contributions that focus on the development and application of novel experimental methods for studying physical, biogeochemical, and ecological conditions at the groundwater-surface water interfaces in rivers, lakes, riparian zones, and wetlands. One of our main interests lies in investigating the role of hyporheic processes in the retention and natural attenuation of nutrients and pollutants, and their influence on surface and groundwater quality. Additionally, we encourage research involving hydrological, biogeochemical, and ecological modeling approaches (e.g. transient storage models, coupled groundwater-surface water models, etc.). Finally, we welcome presentations that investigate the impact of groundwater-surface water interactions on management and risk assessment in view of the European Water Framework Directive.

Droughts, characterized by precipitation deficits and high evaporative demand, are becoming increasingly frequent, prolonged, and intense under global environmental change. Climatic drivers (such as altered precipitation regimes and rising temperatures) and land surface modifications (including vegetation greening, deforestation, land-use transitions, and wildfires) interact in complex ways to shape ecohydrological responses to droughts across spatial and temporal scales.
This session invites contributions that explore how ecosystems and hydrological processes respond to droughts, aiming to uncover both underlying mechanisms and broader consequences. We welcome studies based on observational, modeling, and conceptual approaches. Topics of interest include, but are not limited to:
1. New insights into drought responses based on emerging in-situ and satellite observations of soil moisture, evapotranspiration, and vegetation dynamics.
2. Process-based understanding of ecohydrological responses to droughts of varying severity under changing climate and land surface conditions.
3. Long-term trends and resilience of ecohydrological systems under recurrent droughts, with a focus on resistance, recovery, and key environmental drivers.
4. Advances in modeling frameworks (process-based or AI-based) and observation-constrained approaches for improving the representation of drought responses.
5. Social and ecological impacts of evolving droughts, including implications for ecosystems, agriculture, water resources, and human well-being.
By integrating hydrology, ecology, and remote sensing, this session seeks to advance our understanding of ecohydrological drought responses and to inform sustainable adaptation strategies in a changing environment.

Water may be present in soil, groundwater or surface storage yet remain inaccessible because it is hydraulically disconnected, too saline, too tightly retained, or stored on timescales mismatched with biological or human demand. We define water accessibility as the capacity of stored water to enter ecologically or societally relevant fluxes, with that capacity varying with hydrological state, connectivity, salinity, biological demand and human intervention.
This session asks when, where, for whom and for how long stored water becomes accessible in human-modified critical zones. We welcome studies of mobile and less-mobile domains, preferential flow, soil hydraulic structure, root access, groundwater depth, salinity, wetting-drying transitions, irrigation, drainage, pumping, land-use change, restoration, hydrological memory, water age and transit times.
Contributions may use field or laboratory experiments, stable isotopes and other tracers, geophysics, remote sensing, water-age and transit-time analyses, and a broad range of modelling approaches. We encourage studies addressing accessibility and functional outcomes for transpiration, recharge, runoff, ecological resilience, crop production, water security and other major ecohydrological or societal fluxes.
We particularly encourage work from agricultural systems, wetlands, deltas, drylands, forests, restored landscapes and other human-modified critical zones. Comparative and negative-result studies are welcome, including cases where connectivity or tracer contrasts strengthen, collapse or shift with hydrological state. The aim is to identify measurable indicators, thresholds, trade-offs and management timing while avoiding the assumption that more stored water necessarily means more accessible water.

Vegetation change in mountainous regions is often treated as an outcome of changing hydro-meteorological regimes, yet its feedback to those regimes remains poorly resolved. While it is known that vegetation has significant effects on water partitioning, and shifts in species distributions may actively alter the distribution and temporal availability of water in the regions, these latter dynamics remain poorly represented in the scientific discussion and existing Earth-System-Models. A consolidated understanding of the effects has been hampered by their apparent global heterogeneity: While the European Alps have experienced intensive greening rates, other systems like the North American Rocky Mountains and Sierra Nevada face widespread forest degradation and disturbance driven mortality with varying hydroclimatic impacts.
This session focuses on the underlying and resulting snow-water-vegetation interactions in seasonally and perennially snow-dominated mountain regions across the globe, where runoff generation heavily depends on the seasonality of snow and glacier melt and its interaction with vegetation, surface- and groundwater bodies. We invite contributions addressing the process interactions between snow and glacier melt, surface- and groundwater, evapotranspiration, primary production, soil moisture distribution and runoff generation, welcoming field work as well as modelling studies. We especially look forward to the integration of novel monitoring techniques into modelling frameworks, inviting case studies as well as comparative and scenario studies across space and time.
We want to connect scientists across disciplines to advance ecohydrological understanding of mountain systems and investigate the role of vegetation in these diverse and complex landscapes.