Anthropogenic activities, climate change and poor water resources management lead to insufficient water quality, both biological and chemical, and results in one of the world’s most urgent human health issues. Waterbodies are key for waterborne diseases and water surface water network for spreading of contaminants and diseases. The global health burden could be reduced by improving water supply, sanitation and management of water resources but also by improved understanding of the role of hydrology in transport of pathogens. This scientific session aims to explore the interdisciplinary facets of water cycle and human health in broad sense. By bringing together experts from hydrology, environmental pollution, microbiology, ecology, epidemiology and public health, this session seeks to foster a dialogue to effectively study hydrological processes related to spreading and transmission of diseases and emergent contaminants. The oral part of the session is composed of solicited presentations followed by a panel discussion.

Since the 1980s, various approaches have been developed to address contaminated sites and old landfills, ranging from excavation to advanced in-situ treatment technologies. There is a need post evaluate such sites. While significant progress has been made, ongoing challenges such as the long-term sustainability of these methods and impacts of climate change call for a rethinking of strategies. Emerging contaminants like PFAS (per- and polyfluoroalkyl substances) and microplastics have recently gained attention due to their persistence in the environment and toxicity. New techniques are needed to monitor and treat these. Urban infrastructure projects commonly encounter contaminated soils. For such situations soil washing is becoming an increasingly common ex situ technology to remove contaminants from the soil with a combination of physical separation and chemical leaching by aqueous solutions, creating valuable materials such as gravel and sand. This also reduces the need for waste deposits. Supported by appropriate regulations and sustainability assessment tools, we can push towards a more circular mass handling.

Per- and polyfluoroalkyl substances (PFAS) are a group of man-made chemicals that have been extensively used worldwide for over 80 years due to their unique chemical properties, such as high stability and resistance to degradation. The widespread use of PFAS has led to pervasive contamination in terrestrial and aquatic environments, creating complex regulatory and environmental management challenges.

This session aims to contribute to a comprehensive understanding of PFAS pollution and to share effective strategies for their management and remediation/mitigation. Hence, we aim to bring together researchers and practitioners from diverse fields, including contaminant hydrogeology, environmental chemistry, toxicology, engineering, and policy, to share their insights on the occurrence, behaviour, and management of PFAS in the environment. We primarily seek contributions that explore the latest advancements in understanding PFAS pollution across different environmental matrices, including surface water, groundwater, and soils.

Topics of interest include, but are not limited to:
- The transport and fate of PFAS in terrestrial and aquatic environments,
- Modelling approaches to predict PFAS distribution and transport in various environmental settings,
- Innovative strategies and technologies for the treatment and remediation of PFAS-contaminated water, including drinking water and wastewater,
- Advancements and case studies on the successful application of PFAS remediation/mitigation techniques and their effectiveness in different environmental contexts,
- Ecotoxicological studies,
- Challenges and advancements in regulatory frameworks and policies for managing PFAS pollution, including approaches to identify and mitigate sources of PFAS contamination.

Given the complex nature of PFAS as "forever chemicals" and their ability to partition across different environmental media, this session emphasises the importance of interdisciplinary approaches and collaborative efforts to tackle the multifaceted challenges they present. We welcome studies that utilise laboratory research, field investigations, and modelling efforts, as well as contributions that discuss the implications of PFAS pollution on public and environmental health, ecological integrity, and regulatory landscapes.

The occurrence of pathogens and of an exponentially increasing number of contaminants in freshwater and estuary environments pose a serious problem to public health. This problem is likely to increase in the future due to more frequent and intense storm events, the intensification of agriculture, population growth and urbanization. Pathogens (e.g., pathogenic bacteria and viruses, antibiotic resistance bacteria) are introduced into surface water through the direct discharge of wastewater, by the release from animal manure or animal waste via overland flow, or, into groundwater through the transport from soil, which subsequently presents potential risks of infection when used for drinking, recreation or irrigation. Contaminants of emerging concern are released as diffuse sources from anthropogenic activities, as discharges from wastewater treatment plants (e.g., trace organic contaminants, PFAS), or occur due to microbial growth (e.g. cyanotoxins), posing a burden on human health. So far, the sources, pathways and transport mechanisms of fecal indicators, pathogens and emerging contaminants in water environments are poorly understood, and thus we lack a solid basis for quantitative risk assessment and selection of best mitigation measures. Innovative, interdisciplinary approaches are needed to advance this field of research. In particular, there is a need to better understand the dominant processes controlling fecal indicator, pathogen and contaminant fate and transport at larger scales.

This session aims to increase the understanding about the dominant processes controlling fecal indicator, pathogen and contaminant fate and transport at larger scales. Consequently, we welcome contributions that aim to close existing knowledge gaps and include both small and large-scale experiments, with the focus on
- the fate and transport of fecal indicators, pathogens, emerging contaminants including persistent and mobile organic trace substances (e.g. antibiotic resistance bacteria, cyanotoxins, PFAS) in rivers, soils, groundwater and estuaries
- Hydrological, physically based modelling approaches
- Methods for identifying the dominant processes and for transferring transport parameters of fecal indicators, pathogens and contaminants from the laboratory to the field or catchment scale
- Investigations of the implications of contamination of water resources for water safety management planning and risk assessment frameworks

This session is dedicated to the comprehensive investigation of small-scale transport processes governing the movement of plastics (ranging from micro- to macroplastics) within the aquatic environment. While we aim to place special emphasis on laboratory experiments and modeling approaches, we also welcome presentations employing additional methodologies such as field work, and contributions focused on theoretical concepts.

The presentations will revolve around understanding and characterizing plastic movement, considering influential factors like particle size, shape, density, and environmental conditions such as temperature, salinity, flow velocities, water turbulence and suspended sediment concentrations. Additionally, relevant biological and chemical processes will be taken into account. Key processes to be addressed include sedimentation, resuspension, biofouling, aggregation and fragmentation, along with other interactions between plastics and the environment that may influence the transport and ultimate fate of plastic pollutants.

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 modeling approaches tailored to simulate the intricate transport dynamics of plastics in aquatic 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 endeavors in this vital area of study.

This session is devoted to the study of fate and transport processes of micro and nanoplastic (MNP) particles in soil and groundwater systems. While MNPs in marine and aquatic environments have received considerable interest by the scientific community over the last decade, soil and groundwater environments are comparably understudied and MNP transport and fate in these compartments is less well understood.

We welcome contributions that provide a comprehensive overview on the problem of soil and groundwater MNP contamination from local to global scales. Additionally, we are looking forward to contributions around field sampling, lab processing and characterization techniques specific to MNP in soil and groundwater compartments, as well as to experiments and modelling studies that advance our theoretical understanding of how MNP as well as their leachtes interact with soil and groundwater ecosystems and influence their biochemistry.

With this session we strive to extend our knowledge on MNP fate, transport and interaction with soil and groundwater environments with a diverse range of hydrological and biochemical characteristics including soil type, grain size, hydraulic connectivity, flow velocity and groundwater recharge capacity, organic matter content and microbial activity or soil chemistry. We hope that a better understanding of MNP pathways through the subsurface will aid us in conceptualising potential exposure hazards and pollution risks of vital soil and groundwater resources.

Effective and enhanced hydrological monitoring is essential for understanding water-related processes in our rapidly changing world. Image-based river monitoring has proven to be a powerful tool, significantly improving data collection, analysis, and accuracy, while supporting timely decision-making. The integration of remote and proximal sensing technologies with citizen science and artificial intelligence has the potential to revolutionize monitoring practices. To advance this field, it is vital to assess the quality of current research and ongoing initiatives, identifying future trajectories for continued innovation.

We invite submissions focused on hydrological monitoring utilizing advanced technologies, such as remote sensing, AI, machine learning, Unmanned Aerial Systems (UAS), and various camera systems, in combination with citizen science. Topics of interest include, but are not limited to:

• Disruptive and Innovative sensors and technologies in hydrology.
• Advancing opportunistic sensing strategies in hydrology.
• Automated and semi-automated methods.
• Extraction and processing of water quality and river health parameters (e.g., turbidity, plastic transport, water depth, flow velocity).
• New approaches to long-term river monitoring (e.g., citizen science, camera systems—RGB/multispectral/hyperspectral, sensors, image processing, machine learning, data fusion).
• 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 specific contexts.

The goal of this session is to bring together scientists working to advance hydrological monitoring, fostering a discussion on how to scale these innovations to larger applications.

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

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.

The interaction between the soil-plant-atmosphere compartments and human activities is of paramount importance for the sustainable management and preservation of ecosystem functions and services. The functionality and services of terrestrial ecosystems are threatened by global climate change and human activities. The complexity and comprehensiveness of the impacts have so far proven challenging to assess due to the limitations of simplified experimental approaches and long-term observations, which often focus on a limited number of response variables.
Experimental systems such as lysimeters or ecotrons provide continuous, high-resolution and high-quality observations of detailed time series, which are crucial for a more accurate determination of the Earth's ecosystem services and functions and for promoting interdisciplinary ecosystem research.
This session will mainly focus on the diversity of ecosystem research using research platforms of lysimeters and ecotrons. We would also like to address the challenges of modelling ecosystem processes, comparison of metrics with other in situ instruments, upscaling approaches from such platforms to larger scales, validation studies (e.g. remote sensing), but also new developments in the field of lysimetry and further development of processing algorithms for interpretation of high temporal resolution lysimeter/ecotron weight data. We welcome contributions that (1) present novelties in the field of lysimeters, (2) assess and compare the functioning and services of terrestrial ecosystems, particularly in relation to climate change, (3) focus on water and nutrient transport processes (4) and greenhouse gases within the soil-plant-atmosphere continuum, (5) develop new techniques for the analysis of lysimeter and ecotron observations, (6) include ecosystem or hydrological modelling approaches using in situ observations from lysimeters or ecotrons.

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 are clear demonstrations of how our planet’s climate is changing, underlining 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, 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) Remote sensing and earth observation 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.

High-resolution hydrometric monitoring of rivers is important because climate change severely affects frequency and magnitude of extreme events and flood/drought risk profiles are changing fast. However, hydrometric monitoring data is scarce and lacks spatial resolution and coverage, particularly in remote and hard-to-reach rivers in alpine, Arctic and tropical regions. Advanced in-situ monitoring technologies have to be combined with satellite earth observation (EO) to obtain accurate, reliable, long-time and spatio-temporally resolved information for effective decision support, risk assessment, investment analysis in the context of climate change adaptation, and operational forecasting, surveillance, and management.

Traditional in-situ hydrometric monitoring of rivers is station-based. Water surface elevation, flow velocity, bed geometry and river discharge are measured using sensors that are installed in-situ, either in direct contact or in close proximity to the flow. In-situ station-based monitoring infrastructure is vulnerable and often fails during extreme flooding events, when the value of information is very high. Station-based monitoring networks lack spatial resolution and have been declining in many regions, particularly in remote and hard-to-reach areas. Data accessibility is increasingly restricted because of growing conflicts between countries over water resources allocation.

This session solicits contributions describing new water observing systems providing key hydrometric variables (e.g. bathymetry, velocity, discharge, water surface elevation, temperature, water quality parameters) at high spatial resolution and coverage, using ground-based, satellite, and/or unoccupied arial system (UAS) platforms. Focus is on the development of innovative monitoring technologies, the combination of in-situ, airborne, and satellite EO datasets, and data use for river modeling and decision support.

The Surface Water and Ocean Topography (SWOT) satellite mission, launched in December 2022, marks a significant advancement in hydrological sciences. It is the first satellite designed to investigate surface water in the global water cycle, and it provides the first comprehensive view of Earth's freshwater bodies from space. Using Ka-band radar interferometry, SWOT delivers, for the first time, simultaneous, high-resolution measurements of water surface elevation and inundation extent in rivers, lakes, reservoirs, and wetlands globally. This dataset will fundamentally transform our ability to understand surface water and reveal new insights into hydrologic processes. The hydrologic remote sensing community has worked for more than a decade to develop new methods and scientific understanding that are now allowing SWOT data to advance knowledge of global water fluxes. For this session, we solicit abstracts presenting recent advances enabling SWOT to unlock new frontiers in hydrology and enhance our understanding of Earth’s surface water.

The moment when hydrology became recognised and established as a science remains a topic of debate. Certainly, there is a long tradition of theories on the natural occurrence, distribution, and circulation of water on, in, and over the surface of the Earth (Horton, 1931). While some of these theories remain valid today, others have been replaced by more recent understandings, which reflect the evolution of hydrology as a science.
As a scientific hydrological community, we are committed to advancing our field. Progress in hydrology can greatly benefit from a solid historical foundation, enabling us to assess past achievements, identify research gaps, and learn from earlier missteps. Accordingly, the newly formed IAHS Working Group on the History of Hydrology aims to foster a culture of historical hydrological literacy to support the growth of hydrological science by connecting it to its roots.
For this session, we welcome contributions that examine the evolution of hydrological concepts over time, how overlooked methods might hold contemporary value, and reflect on the factors that have led to incorrect conclusions, i.e. learn from mistakes. Topics of interest include the history of hydrological models and modelling, including deterministic vs stochastic approaches, optimisation, and diagnostic metrics; land-mark hydrological projects, the management of historical datasets or experimental catchments and their management, and the significant contributions of scientists, especially female hydrologists and other under-represented groups, as well as institutes and organisations. We encourage contributions from countries that are underrepresented in the historical hydrological literature.

The Critical Zone (CZ), encompassing the Earth's outer layer 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 complex zone 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 networks from around the world. Topics of interest include, but are not limited to: Innovative techniques in CZ research and monitoring, including contributions involving observations, modeling, or integration of the two; Advances in understanding soils, hydrology, and biogeochemical cycling within the CZ; Characterization of CZ structure as it varies with depth and environmental factors; Impacts of stressors and environmental change on the CZ; Policy or management implications of CZ research; Development of CZ science networks; and Case studies of successful international CZ collaborations.

The effects of climate change highlight the importance of developing a resilient design approach for buildings, both in dense urban areas and rural communities. Nature-based solutions (NBSs) can help in this as an adaptation measure, providing multiple benefits at building scale. Increasing the applications of green walls and green-blue roofs can reduce heat stress, improve rainwater and wastewater management and drive the communities towards the concept of circular economy and self-subsistence.

This session aims to share and discuss the most recent advances in NBSs that increase building resilience and sustainability in the urban environment. Therefore, we aim for a session including researchers from different fields such as engineering and architecture, natural sciences such as microclimatology and meteorology, and social/psychological science. We encourage also those involved in policymaking to submit a contribution, to have an integrated approach to building development.

Our focus will primarily be on solutions that not only improve routine building management but also make meaningful contributions to the mitigation s of extreme events, like extreme urban heat stress (UHI/heat events) or extreme precipitation events and local flooding. Submissions may include (but not restricted to) contributions on:

- Laboratory, field measurements and numerical modelling studies (like microclimatic or hydrodynamic simulations) on green walls and green-blue roofs and other NBSs for rainwater management, wastewater treatment, thermal control, edible vegetation production, energy production
- Qualitative research like user- or agent-based approaches that investigate the potentials and effects of NBSs for climate change adaptation and improving thermal comfort, and further challenges of the water-energy nexus on this small/building scale.
- Urban areas mapping (e.g. GIS applications) or modelling for buildings urban management (BIM applications)
- Investment and cost return of NBS application to buildings
- Life-Cycle-Assessment (LCA) analysis
- Quantitative analysis on possible sanitary risks innovative wastewater treatment and reuse solutions at local scale
- Buildings retrofitting projects or real-scale applications
- NBS social acceptance
- Impact on human well-being and health

In essence, our session aims to explore the multifaceted aspects of NBSs in the context of building resilience, with particular emphasis on their impact, feasibility, and sustainability.

Many papers have advised on careful consideration of the approaches and methods we choose for our hydrological modelling studies as they potentially affect our modelling results and conclusions. However, there is no common and consistently updated guidance on what good modelling practice is and how it has evolved since e.g. KlemeŠ (1986), Refsgaard & Henriksen (2004) or Jakeman et al. (2006). In recent years several papers have proposed useful practices such as benchmarking (e.g. Seibert et al., 2018), controlled model comparison (e.g. Clark et al., 2011), careful selection of calibration periods (e.g. Motavita et al., 2019) and methods (e.g. Fowler et al., 2018 ), or testing the impact of subjective modelling decisions along the modelling chain (Melsen et al., 2019). However, despite their very justified existence, none of the proposed methods have become quite as common and indispensable as the split sample test (KlemeŠ, 1986) and its generalisation to cross-validation.

This session intends to provide a platform for a visible and ongoing discussion on what ought to be the current standard(s) for an appropriate modelling protocol that considers uncertainty in all its facets and promotes transparency in the quest for robust and reliable results. We aim to bring together, highlight and foster work that develops, applies, or evaluates procedures for a trustworthy modelling workflow or that investigates good modelling practices for particular aspects of the workflow. We invite research that aims to improve the scientific basis of the entire modelling chain and puts good modelling practice in focus again. This might include (but is not limited to) contributions on:

(1) Benchmarking model results
(2) Developing robust calibration and evaluation frameworks
(3) Going beyond common metrics in assessing model performance and realism
(4) Conducting controlled model comparison studies
(5) Developing modelling protocols and/or reproducible workflows
(6) Examples of adopting the FAIR (Findable, Accessible, Interoperable and Reusable) principles in the modelling chain
(7) Investigating subjectivity and documenting choices along the modelling chain and
(8) Uncertainty propagation along the modelling chain
(9) Communicating model results and their uncertainty to end users of model results
(10) Evaluating implications of model limitations and identifying priorities for future model development and data acquisition planning

In an era of climate uncertainty and evolving human influence on natural environments, understanding the dynamics of long-term climatic and hydrologic change has become critical. This session has a focus on real-world case studies and applications, though which we seek to explore the multifaceted implications of climate change on water availability, aquatic environments, and the dynamics of socio-ecological riverine systems.

We invite tangible examples of climate change impact assessments on hydrological and related systems, including resource management, policy and adaptation. We hope to showcase research across diverse geographical regions and varied contexts to facilitate sharing of methods, insights and lessons learned.

Submissions are encouraged across the full spectrum of available techniques, including so-called “bottom-up” approaches to decision making under deep uncertainty. Studies applying novel modelling paradigms, innovative risk assessment frameworks, or characterising multiple (compound) sources of risk are particularly encouraged. By showcasing diversity, we aim to foster a practical understanding of the implications of long-term change, leading to better decision-making for an uncertain future.

Continuous changes in global climate are increasing the intensity, frequency, and duration of climate extremes with deep implications for achieving sustainable and just societal development. Given its extensive global coverage and profound interactions with freshwater resources, agriculture is one of the human activities most exposed to climate extremes. Food systems can be directly impacted by extreme climate events (e.g., droughts, floods, and heatwaves). At the same time, climate extremes can exercise substantial influence on water resource availability (e.g., declines in water availability, water pollution) with cascading implications for the productivity and stability of food systems. These consequences are made more complex by growing reliance on food trade and strong water-food-energy interconnections. To fully understand the rising role of climate extremes within water-food systems, new research is needed that provides quantitative approaches to measure the impacts of climate extremes and identifies and tests feasible solutions to mitigate impacts.
In this session, we call for contributions investigating all aspects of interactions between climate extremes and water-food systems, including determining the extent and magnitude of climate extreme impacts on water-food systems, understanding the mechanisms driving the changes of water-food systems under climate extremes, and proposing nature-based or human intervention solutions to mitigate these climate extreme challenges.

Increasing magnitude, duration and frequency of extreme temperatures (high and low) that can impact the quality and quantity of water resources necessitate a clear understanding of their interactions. This session aims to address the multifaceted causes and consequences of temperature extremes on water resources (both quality and quantity). We seek to understand, model and predict water resources’ responses to temperature-induced hazards (e.g., heatwave, cold spell, drought and wildfire) in current and future climates. We welcome novel methodologies, including experimental studies, field measurements, remote sensing and modeling under various temperature-water use scenarios considering physical, environmental, social and economic aspects.
This session invites submissions on (but not limited to): (I) Novel research on impacts of temperature extremes such as heat waves, cold waves, droughts and wildfires or their combination as compound events on water quantity and quality; (II) Proper frameworks, including modeling (physical, statistical/stochastic, data-driven models particularly machine learning), instrumentation, datasets (field, remote sensing), indicators and measures, to predict and manage causes and effects of temperature-induced hazards on water resources; (III) Innovative methods for vulnerability, resilience and impact assessment of temperature-related water resources hazards; (IV) Risk assessment frameworks for managing impacts of temperature extremes (due to climate change and anthropogenic forcing e.g., LULC changes, urbanization, improper management) on water resources; (V) Uncertainty analysis in the context of temperature-induced hazards, offering insights into how uncertainty can be quantified, managed and communicated; (VI) Case studies with different physical features, particularly water-stressed regions to analyze water scarcity and related challenges for areas that are most vulnerable to temperature-induced hazards; (VII) Assessment and development of water policy and water management plans to adapt to changes and mitigate impacts.
By bringing together experts from various fields, the session will contribute to a deeper understanding of the complex interactions between temperature extremes and water resources, ultimately informing decision support systems and sustainable management plans. We encourage students, scientists, researchers, stakeholders and policymakers to submit their abstracts and join us in exploring this vital challenge.

This session welcomes cross-cutting advances in theoretical, methodological and applied studies at the synergistic interface among physical, analytical, information-theoretic, kinematic-geometric, machine learning, artificial and systems intelligence approaches to complex system dynamics, hazards and predictability across Hydrology and broader Earth System Sciences.

Special focus is given to unveil complex system dynamics, regimes, transitions, extremes, hazards and their interactions, along with their physical understanding, predictability and uncertainty, across multiple spatiotemporal scales.

The session encourages discussion on interdisciplinary physical and data-based approaches to system dynamics across Hydrology and broader Geosciences, ranging from novel advances in stochastic, computational, information-theoretic and dynamical system analysis, to cross-cutting emerging pathways in information physics, artificial and systems intelligence with process understanding in mind.

The session further encompasses practical aspects of working with systems intelligence and emerging technological approaches for strengthening systems analytics, causal discovery, model design and evaluation, predictability and uncertainty analysis, along with geophysical automated learning, model design, prediction and decision support.

Take part in a thrilling session exploring and discussing promising avenues in system dynamics and information discovery, quantification, modelling and interpretation, where methodological ingenuity and natural process understanding come together to shed light onto fundamental theoretical aspects to build innovative methodologies to tackle real-world challenges facing our planet.

Water stored in the snowpack and in glaciers represents an important component of the hydrological budget in many regions of the world, as well as a sustainment to life during dry seasons. Predicted impacts of climate change in catchments covered by snow or glaciers (including a shift from snowfall to rainfall, a modified total amount of precipitation, an earlier snowmelt, and a decrease in peak snow accumulation) will reflect on water resources availability for environment and anthropogenic uses at multiple scales. This may have potential implications for energy, drinking water and food production, as well as for environmentally targeted water management.

The generation of runoff in catchments that are impacted by snow or ice profoundly differs from rainfed catchments. And yet, our knowledge of snow/ice accumulation and melt patterns and their impact on runoff is highly uncertain, because of both limited availability and inherently high spatial variability of hydrological and weather data in such areas.

Contributions addressing the following topics (but not limited to) are welcome:
- Experimental research on snowmelt & ice-melt runoff processes and potential implementation in hydrological models;
- Development of novel strategies for snowmelt runoff modelling in various (or changing) climatic and land-cover conditions;
- Evaluation of remote-sensing or in-situ snow products and application for snowmelt runoff calibration, data assimilation, streamflow forecasting or snow and ice physical properties quantification;
- Observational and modelling studies that shed new light on hydrological processes in glacier-covered catchments, e.g. impacts of glacier retreat on water resources and water storage dynamics or the application of techniques for tracing water flow paths;
- Studies addressing the impact of climate change and/or extreme events (e.g., droughts) on the water cycle of snow and ice affected catchments.
- Studies on cryosphere-influenced mountain hydrology and water balance of snow/ice-dominated mountain regions;
- Use of modelling to propose snowpack, snowmelt, icepack, ice melt or runoff time series reconstruction or reanalysis over long periods to fill data gaps;

Despite only representing about 25% of continental land, mountains are an essential part of the global ecosystem. They are also recognised as the source of much of the world's fresh water supply. A significant portion of the global population relies on their water supply, with around 26% living in mountain communities and 40% living in the downstream plains. Mountains are particularly sensitive to climate variability and change due to the heterogeneity of elevation-dependent hydro-meteorological conditions. This makes them unique areas for identifying and monitoring the effects of global change.

This session will bring together the scientific community developing hydrology research on mountain ranges across the globe to share results and experiences. We invite contributions addressing past, present and future changes in mountain hydrology due to changes in climate and/or land use, how these changes affect local and downstream territories, and adaptation strategies to ensure the long-term sustainability of mountain ecosystem services, with a special focus on water cycle regulation and water resources generation. Example topics of interest to this session are:

- Sources of information for evaluating past and present conditions (in either surface and/or groundwater systems).
- Methods for differentiating climatic and anthropogenic drivers of hydrological change.
- Modelling approaches to assess hydrological change.
- Evolution, forecasting and impacts of extreme events.
- Case studies on adaptation to changing water resources availability.

Mountains receive and produce a high proportion of precipitation and runoff, forming the headwaters of many of the world’s major river systems and supplying water to at least half of humanity. These headwaters contain substantial snow and ice reserves and generally are undergoing amplified global warming resulting in rapid changes in landcover, permafrost, snowcover, glaciers, and hydrological regime. Because of the above, high mountain headwaters are the focus of global concern as exemplified by the UN International Year of Glaciers’ Preservation – 2025. Understanding and prediction of the mountain cryosphere and water cycle have been restricted by sparse observation networks, uncertainties in process representation and low model resolution, and substantial heterogeneity over small spatial scales. This session addresses the following questions: How can snow and ice hydrology best be measured in various alpine regions? How do land surface energy and water exchanges differ in various high mountain regions of the Earth? What improvements to high mountain hydrological predictability are possible in various alpine regions through improved process physics, representation of spatial variability, and incorporation of ground and remote observations? To what extent are existing model routines valid and transferrable amongst different alpine regions? Submissions that deal with observations and data, model application and diagnostic comparisons, new process understanding and insights, and better prediction of the changing mountain cryosphere and water cycle are welcome. This session is organized by and contributes to the International Network for Alpine Research Catchment Hydrology (INARCH; https://inarch.usask.ca/) of the World Climate Research Programme’s GEWEX Project.

Water resources are a strategic issue in drylands globally as these environments are by definition water-limited, making them highly sensitive to changes in regional water balances and vulnerable to extreme events such as droughts and floods. Drylands face challenges from changing hydrological conditions and landscapes, driven by climatic and anthropogenic factors, affecting freshwater availability and quality. However, many aspects of the functioning of these systems are poorly understood or often treated in a disciplinary manner. Yet, interdisciplinary research is essential to improve the understanding of hydroclimatic processes in these regions and the human impacts on water resources, to achieve sustainable development goals. We welcome submissions focusing on processes in dryland research across a broad geographical range, from Mediterranean drylands to hyperarid deserts, to build an interdisciplinary session including topics such as:
Estimation of the spatiotemporal variability of water fluxes: rainfall, soil moisture, evapotranspiration, floods and droughts
Hydro-geomorphological impacts of extreme events
Transport and deposition of river sediments and their impact on channel morphology
Groundwater recharge process estimation
Quantification of the impacts of anthropogenic water abstraction?
Climate dynamics and their influence on dryland water balance including paleo-reconstructions and projected future scenarios
Transmission losses and intermittent stream functioning

A large proportion of the global stream network ceases to flow periodically. These systems range from near-perennial streams with infrequent, short periods of zero flow to streams that experience flow only episodically after large rainfall events. The onset of streamflow in intermittent streams can affect the quantity and quality of water in downstream perennial rivers. Intermittent streams also support a unique and high biodiversity because they are coupled aquatic-terrestrial systems. However, non-perennial rivers and streams are usually unmonitored and often lack protection and adequate management. There is a clear need to study the hydrology, biogeochemistry and ecology of natural intermittent and ephemeral streams to characterize their flow regimes, to understand the main origins of intermittence and how this affects biogeochemistry and biodiversity, and to assess the consequences of altered flow intermittence due to climate change or other anthropogenic impacts.
This session welcomes all contributions on the science and management of non-perennial streams, and particularly those highlighting:
· current advances in monitoring flow intermittence, both in-situ and with remote sensing,
· novel approaches and applications in modelling non-perennial reaches, networks and catchments,
· the effects of flow in non-perennial streams on downstream perennial stream water quantity and quality,
· the factors that affect the dynamics of the flowing stream network,
· land use and climate change impacts on flow intermittence,
· links between flow intermittence and biogeochemistry and/or ecology.
· public perceptions (and natural capital/ecosystem services) of non-perennial rivers,
· approaches to determine reference conditions on non-perennial rivers.

The African continent is experiencing various impacts of climate induced sequential droughts, floods, heatwaves, and alteration between two extremes. These changes are causing water and food insecurity across the region. Advances in hydrological models, including process- and machine learning- based models, in better reproductions of observed variables such as streamflow and water availability are improving predictions of socio-economic risks of floods, droughts, and water stress. However, in data-sparse regions, the use of hydroclimatic models for disaster risk reduction still faces unsolved challenges.

This session aims to bring together communities working on different strands of African hydrology, climate risks, water and food security, and environmental risks. We welcome both fundamental and applied research in the areas of hydrological process understanding, monitoring, drought/flood forecasting, seasonal to decadal forecasting, water resources management, climate change and impact assessments including compound and multi-hazard risks. We particularly welcome interdisciplinary studies that combine the physical drivers of water-related risks and their socio-economic impacts. Science for solution initiatives contributing to the IAHS HELPING decade are welcome.

The Danube River Basin (DRB) is one of the most diverse transboundary river system in the world in terms of the number of countries that share over its territory with different natural, cultural, societal and economic backgrounds. The assessment of quantity and quality of water resources and their changes in such a diverse system requires transnational and interdisciplinary approaches and cooperation.
We welcome contributions demonstrating:
(1) Modeling and inter-comparison of different models for simulating water balance components and water quality including climate change impact studies, sensitivity analyses, uncertainty evaluations.
(2) Evaluation of performance and uncertainty of transboundary datasets of climate and hydrological characteristics, including remote sensing products and climate projections.
(3) Applications supporting sustainable management of transboundary water including water abstractions, water-savings or water retention solutions in agriculture and industry.

Transboundary waters encompass aquifers, lakes, and river basins shared by two or more countries. These waters do not adhere to political boundaries, meaning that pollution or overexploitation in one region can have far-reaching consequences beyond borders. Effective transboundary water management is crucial to address pressing issues from water scarcity and biodiversity protection to economic growth and peacekeeping. Over half of the global population resides in transboundary basins. With 286 transboundary river and lake basins covering nearly half of the Earth’s surface, and 592 identified transboundary aquifers, the need for cooperative management is urgent. Given the diverse physical, political, and socio-economic contexts of these shared water bodies, no single approach can solve transboundary water issues. Instead, a suite of practices is required to foster cooperation and ensure sustainable management.
We invite submissions with a focus on (but not limited):
1. Approaches to Assessing Water Quantity and Quality: methods ranging from traditional hydrological models to innovative AI approaches and hybrid applications. We encourage case studies that demonstrate successful application in various transboundary contexts.
2. Remote Sensing Technology Applications: We seek contributions that explore how remote sensing can help close the transboundary water data gap, offering cost-effective, scalable solutions for monitoring and assessing water resources across borders.
3. Development of Joint Monitoring and Information Systems: submissions creating and implementing joint monitoring systems, such as GIS-based databases, that facilitate effective cooperation in water-related risk reduction and transboundary resilience modeling.
4. Water Resources Management Strategies: development and follow-up of water management strategies in transboundary basins. This includes experiences with joint problem definition, creating a common understanding, and evaluating the effectiveness of implemented strategies.
5. Multi-Level Stakeholder Involvement: experiences highlighting multi-level stakeholder engagement in shared water management. This includes capacity development, voluntary data collection through citizen science, participatory modeling, trust-building, and science-policy-driven decision-making.
The session is organized by the GRANDE-U team “Groundwater Resilience Assessment through iNtegrated Data Exploration for Ukraine” (NSF Awards No. 2409395 and 2409396).

Understanding and representing hydrological processes is the basis for developing and improving hydrological and Earth system models. Relevant hydrological data are becoming globally available at an unprecedented rate, opening new avenues for modelling (model parametrization, evaluation, and application) and process representation. As a result, a variety of models are developed and trained by new quantitative and qualitative data at various temporal and spatial scales.
In this session, we welcome contributions on novel frameworks for model development, evaluation and parametrization across spatio-temporal scales.

Potential contributions could (but are not limited to):
(1) introduce new global and regional data products into the modeling process;
(2) upscale experimental knowledge from smaller to larger scale for better usage in catchment models;
(3) advance seamless modeling of spatial patterns in hydrology and land models using distributed earth observations;
(4) improve model structure by representing often neglected processes in hydrological models such as human impacts, river regulations, irrigation, as well as vegetation dynamics;
(5) provide novel concepts for improving the characterization of internal and external model fluxes and their spatio-temporal dynamics;
(6) introduce new approaches for model calibration and evaluation, especially to improve process representation, and/or to improve model predictions under changing conditions;
(7) develop novel approaches and performance metrics for evaluating and constraining models in space and time

This session is organized as part of the grass-root modelling initiative on "Improving the Theoretical Underpinnings of Hydrologic Models" launched in 2016.

Stable and radioactive isotopes as well as other natural and artificial tracers are useful tools (i) to fingerprint the sources of water and solutes in catchments, (ii) to trace flow pathways or (iii) to quantify exchanges of water, solutes and particulates between hydrological compartments. We invite contributions that demonstrate novel applications and recent developments of isotope and other tracer techniques in hydrological field studies and 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.

Significant advance in the understanding of water transit times, subsurface structure controls on biogeochemical reactions, and the quantification of catchment scale weathering rates have resulted in the convergence of biogeochemical and hydrological frameworks. Although such convergence is necessary for a mechanistic understanding of the Critical Zone, many challenges still exist. Perhaps the most difficult of all is to reach a unifying hydro-biogeochemical theory that can compare catchments across gradients of climate, geology, and vegetation, while also considering the compositional nature of geochemical data. Understanding the processes driving the evolution of chemical tracers as they move through space and time is of cardinal importance to validating hypotheses regarding Critical Zone features such as the residence time of water in catchments, concentration-discharge relationships, or nutrient cycling through ecosystems. This session aims to initiate and/or intensify exchanges between two of the main scientific fields in Critical Zone science: hydrology and biogeochemistry. We are expecting novel approaches that allow merging hydrological modelling with studies of biogeochemical 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

Maintaining good water quality is essential for preserving the ecological, recreational, and industrial functions of our water resources. This quality is mainly controlled by the catchment properties and hydro-meteorological conditions, with land use and climate change significantly altering the quantities and dynamics of particulate and solute concentrations at the catchment outlet. To address these influences, water quality is typically monitored and assessed at the catchment scale. However, effective measures to prevent or reduce water quality deterioration are still hindered by our limited understanding of the underlying processes and causal relationships resulting from the complex interplay of hydrological, biogeochemical, and temporal factors.
Data-driven statistical analysis of discharge and concentration time series observed at catchment outlets provides valuable insights into the underlying mechanisms, including process scaling and the effectiveness of measures. The growing availability of data from long-term, high-temporal and high-spatial resolution monitoring of water quality can inform experimental and modeling studies, allowing us to progress from recognizing patterns to the understanding and also modeling of processes. A profound understanding of solute and particulate mobilization, retention, and export mechanisms ultimately allow us to develop local or catchment-scale solutions to mitigate negative impacts on water quality.
This session brings together contributions focused on analyzing or modeling solute and particulate export dynamics at the catchment scale with those focused on the development of mitigation measures or other solutions to enhance or protect water quality.
Examples include solute or particulate export patterns and C-Q relationships under variable hydro-meteorological conditions or contrasting landscapes, mitigation measures based on best practices as well as innovative measures under development or tested under lab-scale conditions.

Agricultural activity has a significant impact on the environment, starting with the clearing of natural land for cultivation. This process disrupts the hydrological cycle and increases the risk of laminar erosion in rills and gullies. Erosion also occurs during tillage and harvesting, while agrochemicals contaminate soils, as well as surface and groundwater. Additionally, a large portion of available water resources is consumed for irrigation.

Addressing these challenges is crucial for the future of humanity. A comprehensive approach requires a productive balance between direct data and observations, along with modeling tools, as data is essential for accurate model evaluation.

This session aims to explore several key areas, at the agricultural watershed scale: the characterization of hydrological, erosive, and agrochemical export behavior in agricultural watersheds worldwide; problem diagnosis; new technologies and sensors for monitoring these variables; innovative watershed modeling techniques to evaluate the impact of agriculture on water quality and soil erosion; and the identification of scenarios, through modeling, that minimize the adverse effects of agricultural practices. The ultimate goal is to foster more sustainable and environmentally responsible agriculture.
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Agriculture impacts the environment by disrupting the hydrological cycle, causing erosion, and polluting water with agrochemicals. This session covers key areas like watershed monitoring, innovative modeling techniques, and solutions to minimize negative effects, aiming for sustainable agriculture.

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

Quantifying and understanding the impacts of global change (climate change and extremes, land use change and socio-economic developments) on clean water availability across space and time is critically important for ensuring that there is enough water of suitable quality to meet 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. Thus, 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 address 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 other 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;
• 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 or water security (combining water quality & quantity) supply and demand in the context of a changing climate and other global change drivers;
• quantify the uncertainty of water quality model under drivers of global change;
• interpret and characterize uncertainties in machine-learning, AI and data-mining approaches that are trained on large, possibly high-resolution data sets;
• address the problem of temporal and spatial scaling (e.g. disparity of scales between processes, observations, model resolution and predictions) in water quality modelling;
• test transferability and generalizability of water quality findings;
• involve stakeholders in water quality model development to inform risk analysis and decision support;
• application of remote sensing in water quality estimates at multiple scales.

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)

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.

This session aims to bridge the gap between academia and industry to address the complex challenge of emerging contaminants in the water cycle. By fostering interdisciplinary discussions and intersectorial collaborations, the session will explore sustainable remediation strategies and innovations in the water sector. The session welcomes contributions focusing on circular economy principles, including case studies of water reuse, emerging contaminants removal and recovery from water resources. It seeks to bring together experts from both academia and the industrial sector to share innovative approaches and practical solutions, fostering partnerships that drive progress in the sustainable management of water resources. We seek contributions that can highlight sustainable remediation, emphasizing the need to tackle emerging contaminants with innovative solutions that are scientifically sound, economically viable and sustainable from an environmental viewpoint. The goal is to stimulate a dialogue that not only advances scientific knowledge but also promotes actionable outcomes that benefit society and the environment. Contributions from the academic and industrial sector are welcome, ranging from innovative lab- and pilot-scale studies to computational approaches, innovative remediation case studies, sustainable remediation and water reuse. The session is promoted by the REMEDI project team (Grant ID: 956384), an EU-funded Horizon 2020 ITN focusing on innovative pharmaceutical wastewater treatment methods. REMEDI focuses on X-ray contrast medium agents and trains early stage researchers to address pharmaceutical water contamination, enhancing the topics mentioned above.

The development and intensification of agricultural production has led to excessive large-scale and long-term transfers of pollutants to water bodies across the globe. During the past few decades, we have consequently witnessed the degradation of the quality of groundwater, surface water and estuaries, which threaten exposed humans and ecosystems. Yet, despite billions invested in conservation efforts, only minimal enhancements in water quality have been observed. Indeed, diffuse contaminations present specific challenges in their understanding, monitoring and modeling, which may prevent effective management and regulations. These specific challenges are posed by factors such as an insufficiency of available data, a complex targeted monitoring, a demanding model resolution and parametrization, and the emergence of puzzling phenomena such as legacy effects. To design adapted regulations, there is then an urgent need to, among other, improve the understanding and conceptualization of regional scale water bodies contamination, better strategizing monitoring, and develop accurate and efficient transport models at relevant spatial and temporal scales.
Broadly, this session seeks contributions that moves forward our protection against diffuse contaminations. Focus will specially be on recent advances on the conceptualization, processes understanding and modeling of contaminant transfer from the land through the hydro(geo)logical system. We highly welcome presentations that work towards innovative representation of reactivity at relevant scales, local scale data integration into large scale models, upscaling schemes, and integrated modeling frameworks. This session also encourages discussion on new advances, methods, and approaches for quantifying contamination dynamics in regional hydro(geo)logical systems in diverse climatic and hydrologic settings.

Floods and droughts have major impacts on society and ecosystems and are projected to increase in frequency and severity with climate change. These events at opposite ends of the hydrological spectrum are governed by different processes that operate on different spatial and temporal scales and require different approaches and indices to characterize them. However, there are also many similarities and links between the two types of extremes which are increasingly being studied.
This session on hydrological extremes aims to bring together the flood and drought communities to learn from the similarities and differences between flood and drought research. We aim to improve the understanding of the processes governing both types of hydrological extremes and their interplay, develop robust methods for modelling and analyzing 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 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. We especially encourage submissions from early-career researchers.

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.

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.

The relationship between land cover, land use, and water resources is complex and bidirectional. Changes in land cover and use can dramatically alter water circulation, availability, quantity and quality, while water resources significantly shape land cover patterns and ecosystem health. Land cover changes are determined by many environmental factors, including water circulation, landscape quality, and ecosystems. Climate variability and land cover changes have been shown to alter the quality and availability of freshwater resources around the world at multiple scales. Human activity is the main driving force influencing land cover changes. Globally, land cover change is a dominant factor affecting ecosystems and the hydrological regime. Land use and land cover changes (LUCC) directly affect the magnitude of evapotranspiration, surface runoff, groundwater recharge by infiltration, and even precipitation. Generally, evapotranspiration, surface water storage, and groundwater recharge are interrelated processes that regulate the balance in the water dynamics of the entire basin. From the point of view of water management, the simulation of land use changes is very important because it provides future scenarios and patterns for water resources.
The main objective of the session is to discuss the role of land use/land cover changes in different regions and diverse scales in accelerating hydrological processes and altering water resources. The main topics should include the following problems:
1. Transitions of LULC changes in different landscapes,
2. Impact of LULC changes on ecosystems and the risk of floods and droughts,
3. Indicators of water resources including LULC changes,
4. Modelling of hydrological processes including LULC changes,
5. Projections of water resource changes affected by LULC and climate change,
6. New data sources to detect LULC changes

Forests are primary regulators of water, energy, and carbon cycles. Maintaining forest functional integrity is fundamental to the sustainability of ecosystems, societies, and human development as described in the UN Sustainable Development Goals.
Global change and anthropogenic intervention are putting enormous pressure on forests, affecting the ecosystem services they provide through water quantity and quality, and biogeochemical cycles. The conventional wisdom that forest hydrology emphasizes the role of forests and forest management practices on runoff generation and water quality has expanded in light of rapid global change.
Improving our understanding of how forest-water interactions are shaped by physiographic, biogeochemical and hydrometeorological factors and how forested catchments respond to dynamic environmental conditions and disturbances, is critical for protecting and managing our forest ecosystems. Building this knowledge requires interdisciplinary approaches in combination with new monitoring methods and modeling efforts.
This session brings together studies that aim to improve our understanding of water-forest dynamics and stimulate discussion on the impact of global change on hydrological processes in forest ecosystems at different scales.
We invite field experimentalists and modelers working in forests from boreal to tropical regions to submit contributions that:
1) Improve our understanding of forest (eco)hydrological processes using an experimental or modeling approach or a combination of both;
2) Assess the hydrology-related impacts of land use/cover change and environmental disturbances on forested ecosystems;
3) Feature innovative methods and observational techniques, such as optical sensors, tracer-based experiments, monitoring networks, citizen science, and drones, that reveal new insights or data sources in forest hydrology;
4) Include interdisciplinary research that supports consideration of overlooked soil-plant-atmosphere components in hydrological studies.

This session focusses on hydrological response to changes in climatic forcing at multi-annual to multi-decadal timescales. Catchments are complex systems responding to changes in climate, among external factors, on a variety of timescales and with many interacting processes. The poor performance of models in representing these responses suggests they potentially misrepresent (or omit) important catchment processes, process timescales, or interactions between processes. To improve hydrological models, the multitude of responses, interactions and feedbacks developing in hydrological systems need to be disentangled and understood. Such insights can originate both from site-specific investigations or from studies that use large datasets and/or models to critique or improve hydrological simulations under changing conditions.
This session covers themes such as (but not limited to):
1. Better understanding of hydrological and/or biophysical processes that govern hydrological response to long-timescale (multi-annual or longer) climate shifts – insights from field and modelling applications;
2. Studies of hydrological regularities (e.g. the Budyko hypothesis) for predictions under changing conditions;
3. Characterising catchment multi-annual “memory” and its representation in models; and
4. Efforts to improve the realism and robustness of hydrological simulations under climatic variability, change and future scenarios.

Large data samples of catchments offer insights into the physiographic and hydroclimatic factors that shape hydrological processes. These datasets increasingly encompass a diverse range of hydrologic conditions, across time and space, facilitating research on a wide variety of topics. This includes testing hypotheses of hydrologic theories, exploring uncertainties in data and models, evaluating interactions within different hydrological model structures, and enabling predictions in ungauged basins.
We welcome abstracts that seek to accelerate progress on the following topics:
1. Development and improvement of large-sample data sets:
How can we address current challenges on the uneven geographical representation of catchments, quantification of uncertainty, catchment heterogeneities and human interventions for fair comparisons among datasets? Can we foster the harmonisation of large-sample data sets? How can we test the representativeness of the available samples? How can we (systematically) represent human influences in large sample datasets?
2. Increase our process understanding:
How can we use large samples of catchments to transfer hydrologic theories (i.e. structural understanding) from well-monitored or experimental catchments to data-scarce catchments? Can currently available global datasets be used to draw improved perceptual models and better define hydrologic similarity?
3.Advance catchment modelling:
How can we improve process-based and machine learning modelling by using large samples of catchments? How can information and knowledge (i.e. functional understanding) be transferred between catchments and applied to data-scarce regions? Furthermore, how can we develop new models and workflows to more effectively leverage these models to infer hydrological response under changing environmental conditions, particularly those influenced by human activities?
4. Hydrologic synthesis:
How can we use catchment descriptors available in large sample datasets to infer dominant controls for relevant hydrological processes? Do we need the definition of new catchment descriptors or the inclusion of new variables? How can we improve our classification of catchments, of their connectivity and of their hydrologic processes?

Floods are extreme events that cause huge losses of lives and properties. As the consequences of climate change intensify, novel approaches in hydrology have become essential for developing robust flood risk mitigation strategies that aid in effective water resource management to foster sustainable development. Preparation, monitoring, and planning against the flood requires the generation of tools such as flood forecasting and predicting extreme flood events under climate change. The present session solicits novel contributions from the researchers to investigate and manifest revolutionary developments in the catchment hydrology by utilizing cutting-edge technologies such as Artificial Intelligence (AI), remote sensing, and process-based modeling. The combined use of these technologies is revolutionizing flood modeling and management methods and providing new avenues to analyze complicated hydrological processes that would improve the ability of ecosystems to adapt and recover from the impacts of climate change and challenges.

This session aims to bring together professionals from hydrology sciences and engineering to share their valuable and innovative insights, utilizing modern technologies on a variety of topics, including but not limited to the following:

• The paradigm shifts from conventional to modern learning approaches such as integrated, hybrid, and universal are crucial for the modeling of hydrological extremes.
• Regional modeling approach in hydrology for extreme event prediction in ungauged or poorly gauged basins.
• Real-time monitoring of extreme flood events using remote sensing, but not limited to optical, and Synthetic Aperture Radar (SAR).
• Explore the Physics-based AI, Generative AI (GAI), and Digital Twins including traditional AI in the field of flood risk mitigation.
• Discovering possibilities for integrated and innovative solutions using public participation for Food Risk Mitigation (FRM), including riverine, urban, and Glacial Lake Outburst Floods (GLOFs).
• Integrated watershed management (IWM) strategies that improve decision-making processes for flood mitigation and foster sustainable water resource management.

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 prediction, 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 current and future state of our global and large scale water resources;

(ii) the use of global earth observations and in-situ datasets for large-scale hydrology and data assimilation techniques for large-scale hydrological models;

(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;
(vi) evaluating the effects of climate change, land-use change, and water-use change on global groundwater and implications of large-scale groundwater understanding on monitoring design, integrated water management, and global water policies.

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. Aquifers may span political and natural boundaries, but 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 wells 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:
• Regional to global groundwater-related datasets and big-data assessments
• 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
• Large-scale groundwater assessments related to the fulfillment of the UN sustainable development goals (SDGs)

Different approaches including global models, data-driven approaches, and machine learning are used to assess water balance components at the global, continental, and regional scale. 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) 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. 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 storages/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 analyze water balance components individually or in an integrative manner on global, continental, or regional scales. Assessments of uncertainty in past/future estimates of water balance components and their implications are highly welcome.

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

A known challenge in hydrological science is the robust uncertainty analysis of physical processes through analysis of records from regional and global scale ground, coastal and marine observations (on point basis or gridded), satellite and reanalysis data, remote-sensed records, laboratory measurements and computational outputs. The stochastic analysis of analogies among hydroclimatic and hydrodynamic processes in a vast range of scales offers insights on coherences und uncertainty (marginal and dependence structures, intermittent and fractal behaviour, trends, irreversibility, etc.). Stochastic approaches can also serve as information for water-related management purposes, natural hazard assessment, and mitigation measures, e.g. in terms of hydrologic design estimation.
This session welcomes, but is not limited to, contributions on stochastic spatio-temporal analysis, modelling, simulation and prediction of hydrological-cycle and hydrodynamic processes (streamflow, precipitation, temperature, evapotranspiration, humidity, dew-point, soil moisture, groundwater, etc.), water-energy-food nexus processes (agricultural, financial and other related fields, solar radiation, wind speed, reservoir stage, etc.), laboratory measurements (i.e., small-scale models for large-scale applications), and computational outputs (e.g., concerning floods, droughts, climatic models, etc.).

In recent years, the field of geostatistics has seen significant advancements, yet the focus on more traditional approaches remains crucial. These methods are fundamental in understanding spatially and temporally variable hydrological and environmental processes, which are vital for risk assessment and management of extreme events like floods and droughts.
This session aims to provide a comprehensive platform for researchers to present and discuss innovative applications and methodologies of geostatistics and spatio-temporal analysis in hydrology and related fields. The focus will be on traditional approaches and the assessment of uncertainties. Machine Learning approaches have specific and dedicated sessions.

We invite contributions that address the following topics (but not limited to):
1. Spatio-temporal Analysis of Hydrological and Environmental Anomalies:
- Methods for detecting and analyzing large-scale anomalies in hydrological and environmental data.
- Techniques to manage and predict extreme events based on spatio-temporal patterns.
2. Innovative Geostatistical Applications:
- Advances in spatial and spatio-temporal modeling.
- Applications in spatial reasoning and data mining.
- Reduced computational complexity methods suitable for large-scale problems.
3. Geostatistical Methods for Hydrological Extremes:
- Techniques for analyzing the dynamics of natural events, such as floods, droughts, and morphological changes.
- Utilization of copulas and other statistical tools to identify spatio-temporal relationships.
4. Optimization and Generalization of Spatial Models:
- Approaches to optimize monitoring networks and spatial models.
- Techniques for predicting regions with limited or unobserved data e.g., using physical-based model simulations or using secondary variables.
5. Uncertainty Assessment in Geostatistics:
- Methods for characterizing and managing uncertainties in spatial data.
- Applications of Bayesian Geostatistical Analysis and Generalized Extreme Value Distributions.
6. Spatial and Spatio-temporal Covariance Analysis:
- Exploring links between hydrological variables and extremes through covariance analysis.
- Applications of Gaussian and non-Gaussian models in spatial analysis and prediction.

The complexity of hydrological and Earth systems poses significant challenges to their prediction and understanding capabilities. The advent of machine learning (ML) provides powerful tools for modeling these complex systems. However, realizing their full potential in this field is not just about algorithms and data, but requires a cooperative interaction between domain knowledge and data-driven power. This session aims to explore the frontier of this convergence and how it facilitates a deeper process understanding of various aspects of hydrological processes and their interactions with the atmosphere and biosphere across spatial and temporal scales.

We invite researchers working in the fields of explainable AI, physics-informed ML, hybrid Earth system modeling (ESM), and AI for causal and equation discovery in hydrology and Earth system sciences to share their methodologies, findings, and insights. Submissions are welcome on topics including, but not limited to:

- Explainability and transparency in ML/AI modeling of hydrological and Earth systems;
- Process and knowledge integration in ML/AI models;
- Data assimilation and hybrid ESM approaches;
- Causal learning and inference in ML models;
- Data-driven equation discovery in hydrological and Earth systems;
- Data-driven process understanding in hydrological and Earth systems;
- Challenges, limitations, and solutions related to hybrid models and XAI.

Deep Learning has seen accelerated adoption across Hydrology and the broader Earth Sciences. This session highlights the continued integration of deep learning and its many variants into traditional and emerging hydrology-related workflows. We welcome abstracts related to novel theory development, new methodologies, or practical applications of deep learning in hydrological modeling and process understanding. This might include, but is not limited to, the following:
(1) Development of novel deep learning models or modeling workflows.
(2) Probing, exploring and improving our understanding of the (internal) states/representations of deep learning models to improve models and/or gain system insights.
(3) Understanding the reliability of deep learning, e.g., under non-stationarity and climate change.
(4) Modeling human behavior and impacts on the hydrological cycle.
(5) Deep Learning approaches for extreme event analysis, detection, and mitigation.
(6) Natural Language Processing in support of models and/or modeling workflows.
(7) Applications of Large Language Models and Large Multimodal Models (e.g. ChatGPT, Gemini, etc.) in the context of hydrology.
(8) Uncertainty estimation for and with Deep Learning.
(9) Advances towards foundational models in the context of hydrology and Earth Sciences more generally.
(10) Exploration of different training strategies, such as self-supervised learning, unsupervised learning, and reinforcement learning.

The session will explore the integration of stakeholder engagement and advanced hydroinformatics techniques such as remote sensing, machine learning, AI, and numerical modeling to address key challenges in hydrological sciences and natural hazards. Emphasizing both theoretical advancements and practical applications, the session will attract contributions from diverse geographic regions and hydrological contexts, particularly those involving the co-development of research with decision-makers.

Key Themes:
1. Hydrological Extremes Monitoring and Prediction:
Utilizing remote sensing and global datasets to monitor and predict droughts, floods, and extreme climatic events, Developing machine learning models for forecasting hydrologic extremes across diverse basins, & Integrating land surface modeling with data assimilation of satellite and in-situ observations.

2. Process Dynamics in Complex Terrain
Modeling land surface hydrology across diverse topographies and climatic zones, Examining the influence of topographic variability on land surface dynamics and hydrological extremes, and Integrating local knowledge with high-resolution data for effective water resource management in mountainous regions.

3. Climate Change Impacts on Hydrology:
Evaluating the influence of climate change on hydrological processes and extremes, including floods and droughts & Applying integrated modeling approaches to understanding the combined effects of land use and climate change on hydrological regimes.

4. Equity in Water Resource Management:
Analyzing trade-offs in water distribution systems, focusing on equity and performance during scarcity & Case studies on the impacts of domestic water storage and rationing under varying climate conditions.

5. Technological Innovations in Hydroinformatics:
Leveraging AI and hydroinformatics tools to enhance water resource management and policymaking & Advances in data assimilation techniques to improve model predictions and decision support systems.

6. Participatory Research and Stakeholder Engagement
Collaborating with decision-makers to co-develop research methods and refine models, ensuring stakeholder-driven processes, Co-designing data analysis and visualization tools to support science-informed decision-making and enhance research relevance, & Case studies that highlight successful science-to-action projects through integrating stakeholder perspectives.

Hydroinformatics has emerged over the last decades to become a recognised and established field of independent research within the hydrological sciences. It is concerned with the development and application of mathematical modelling, information technology, systems science and computational intelligence tools in hydrology. Hydroinformatics nowadays also deals with collecting, handling, analysing and visualising Big Data sourced from remote sensing, Internet of Things (IoT), earth and climate models, and defining tools and technologies for smart water management solutions.
This session aims to provide an active forum in which to demonstrate and discuss the integration and appropriate application of emergent techniques and technologies in water-related contexts.
Topics addressed in the session include:
* Predictive and exploratory models based on the methods of statistics, computational intelligence, machine learning and data science: neural networks, fuzzy systems, genetic programming, cellular automata, chaos theory, etc.
* Methods for analysing Big Data and complex datasets (remote sensing, IoT, earth system models, climate models): principal and independent component analysis, time series analysis, clustering, information theory, etc.
* Optimisation methods associated with heuristic search procedures (various types of genetic and evolutionary algorithms, randomised and adaptive search, etc.) and their application to hydrology and water resources systems
* Multi-model approaches and hybrid modelling approaches that blend process-based (mechanistic) and data-driven (machine learning) models
* Data assimilation, model reduction in integrated modelling, and High-Performance Computing (HPC) in water modelling
* Novel methods for analysing and quantifying model uncertainty and sensitivity
* Smart water data models and software architectures for linking different types of models and data sources
* IoT and Smart Water Management solutions
* Digital Twins for hydrology and water resources
Applications could belong to any area of hydrology or water resources, such as rainfall-runoff modelling, hydrometeorological forecasting, sedimentation modelling, analysis of meteorological and hydrologic datasets, linkages between numerical weather prediction and hydrologic models, model calibration, model uncertainty, optimisation of water resources, smart water management.

We welcome abstracts on new observational systems for hydrosphere processes aiming to build digital twins for water management including atmosphere, soil, surface water or groundwater systems and related infrastructure. Improved monitoring of hydrological storages and fluxes is crucial for the development of new observational systems, modelling and analysis platforms. The processes measured on land, surface water and subsoil water, with novel technologies and integrated modelling platforms open new possibilities to observe the hydrosphere in various temporal scales, from sub-daily to long-term trends and extremities. Remotely sensed data including in-situ and mobile sensors are essential data source to support a digital revolution in hydrosphere processes studies and river basin management. We welcome presentations on digital twin development of different complexities and maturity levels for diverse water systems (river, groundwater, farmland, urban). Moreover, we welcome presentations on applications that integrate hydrological processes in natural and built environments for improved integrated water management using digital solutions to simulate reality and the various management challenges.

Predictions of physical, chemical, and biological processes in soils, aquifers, rivers and across compartments are strongly affected by uncertainties and errors in model structure, parameters and forcing data. Thus, finding new model formulations (data-driven, physics-based, knowledge-guided or hybrid), estimating parameter sets, quantifying uncertainty, correcting for errors and evaluating competing models are crucial for reliable predictions at any scale (lab/field/catchment). We invite contributions on improved concepts, approaches and computational algorithms in these areas, especially on:
- new methods for inference of model equations or their parameters, inverse modelling and data assimilation in spatially distributed systems,
- data worth and optimal experimental design strategies that maximize information from (computational) experiments and minimize uncertainty,
- novel theories and concepts for spatial and temporal analysis of model - data mismatches,
- formal and informal frameworks that diagnose, detect and resolve modelling errors and capture conceptual model uncertainty,
- approaches how to bring (and extract) sound scientific reasoning into machine learning, be it for inferring new models, model error correction or data analysis,
- constraint learning techniques and novel likelihood formulations as methods to incorporate expert knowledge and soft information into the model/parameter inference process,
- new measurement technologies (point-scale to remote sensing and “soft information”) that aid developing, learning or parameterizing models, or can help diagnose and detect structural model deficiencies, as well applications and benchmarking efforts in any of these fields.
- Bayesian approaches that address any of the topics above

Proper characterization of uncertainty remains a major research and operational challenge in Environmental Sciences and is inherent to many aspects of modelling impacting model structure development; parameter estimation; an adequate representation of the data (inputs data and data used to evaluate the models); initial and boundary conditions; and hypothesis testing. To address this challenge, methods that have proved to be very helpful include a) uncertainty analysis (UA) that seek to identify, quantify and reduce the different sources of uncertainty, as well as propagating them through a system/model, and b) the closely-related methods for sensitivity analysis (SA) that evaluate the role and significance of uncertain factors (in the functioning of systems/models).

This session invites contributions that discuss advances, both in theory and/or application, in methods for SA/UA applicable to all Earth and Environmental Systems Models (EESMs), which embraces all areas of hydrology, such as classical hydrology, subsurface hydrology and soil science.

Topics of interest include (but are not limited to):
1) Novel methods for effective characterization of sensitivity and uncertainty
2) Analyses of over-parameterised models enabled by AI/ML techniques
3) Single- versus multi-criteria SA/UA
4) Novel methods for spatial and temporal evaluation/analysis of models
5) The role of information and error on SA/UA (e.g., input/output data error, model structure error, parametric error, regionalization error in environments with no data etc.)
6) The role of SA in evaluating model consistency and reliability
7) Novel approaches and benchmarking efforts for parameter estimation
8) Improving the computational efficiency of SA/UA (efficient sampling, surrogate modelling, model identification and selection, model diagnostics, parallel computing, model pre-emption, model ensembles, etc.)
9) Methods for detecting and characterizing model inadequacy

Heavy precipitation in small- to medium-sized catchments causes several hazards, including surface water floods (prior to water entering drainage networks or streams) or flash floods, erosion and sediment transport, debris flows and shallow landslides, which may all result in catastrophic risks.
Enhancing the anticipation of such hazards is crucial for effective crisis management and eventually reducing the losses. Nonetheless, numerous challenges still exist regarding their temporal and spatial predictability. Firstly, the rapid development of triggering rainfall events, the scarcity of suitable observations, and the high variability and non-linearity of the physical processes can generate significant uncertainty. Additionally, the concurrent occurrence of multiple hazards, the substantial variability in societal exposure, and the intricacies of socioeconomic vulnerability complicate the assessment of overall potential risks.
This session aims to illustrate current advances in monitoring, modeling, and short-range forecasting of rainfall-induced surface water floods, flash floods, and associated geomorphic hazards including their impacts. Contributions to the following scientific themes are specifically expected:
- Monitoring and nowcasting of heavy precipitation events based on radar and remote sensing (satellite, lightning, ..), to complement rain gauge networks
- New direct and indirect (proxy data) observation techniques and strategies for the observation or monitoring of rainfall-induced-hazards, and the validation of forecasting approaches.
- Short-range heavy precipitation forecasting based on Numerical Weather Prediction models, with a focus on seamless forecasting strategies, and ensembles for the representation of uncertainties.
- Development of integrated short-range hydro-meteorological forecasting chains and new modeling approaches for predicting rainfall-induced hazards in gauged and ungauged basins
- Understanding and modeling of surface water floods, flash floods, geomorphic processes, impacts, and their cascading effects, at appropriate space-time scales
- Risk modeling and forecasting approaches, including inundation mapping, damages modeling, and/or specific impacts modeling approaches for the representation of societal vulnerability.
- Assessing changes of rainfall induced hazards due to the coexistence with other types of hazards.

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 of water scarcity, particularly in regions that are already water-stressed, and where overexploitation of available water resources can exacerbate the consequences droughts have. This may lead to (long-term) environmental and socio-economic impacts. Drought Monitoring and Forecasting are recognised as one of three pillars of effective drought management, and it is, therefore, necessary to improve both monitoring and sub-seasonal to seasonal forecasting for droughts and water availability, and to develop innovative indicators and methodologies that translate the data and information to underpin effective drought early warning and risk management.

This session addresses statistical, remote sensing, 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, groundwater levels, and the propagation of drought through the hydrological cycle. The development and implementation of drought indicators meaningful to decision-making processes, and ways of presenting and integrating these with the needs and knowledges of water managers, policymakers and other stakeholders, are further issues that are addressed and are invited to submit to this session. Contributions focusing on the interrelationship and feedbacks between drought, 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 in the fields of water resources and drought risk management. Particularly welcome are applications and real-world case studies, both from regions that have long been exposed to significant water stress, as well as regions that are increasingly experiencing water shortages due to drought and where drought warning, supported by state-of-the-art monitoring and forecasting of water resources availability, is likely to become more important in the future.

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

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, 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).

The Early Warning for All initiative in alignment with the Sendai Framework for Disaster Risk Reduction (SFDRR) recognizes that increased efforts are required to develop life-saving risk-informed and impact-based multi-hazard early warning systems. Despite remarkable advances in disaster forecasting and warning technology, it remains challenging to produce useful forecasts and warnings that are understood and used to trigger early actions. Overcoming these challenges requires progress that goes beyond the improved skill of natural hazard forecasts. It is crucial to ensure that forecasts reflect on-the-ground impacts, provide actionable information and to understand which implementation barriers exist to do so. This, in turn, requires commitment to the creation and dissemination of risk and impact data as well as the collaborative production of impact-based forecasting services. To deal with these challenges, novel science-based frameworks have recently emerged. For example, Forecast-based Financing and Impact-based Multi-Hazard Early Warning Systems are currently being implemented operationally by both governmental and non-governmental organisations in several countries. This achievement is the result of a concerted international effort by academic, governmental/intergovernmental and humanitarian organizations to reduce disaster losses and ensure reaching the objectives of SFDRR. This session aims to offer valuable insights and share best practices on impact-based multi-hazards early warning systems from the perspective of both the knowledge producers and users. Topics of interest include, but are not limited to:
● Practical applications and use-cases of impact-based forecasts
● Development of cost-efficient early action portfolios
● Methods for translating climate-related and geohazard forecasts into actionable impact-based information
● Action-oriented forecast verification and post-processing techniques to tailor forecasts for early action
● Triangulation of indigenous and scientific knowledge for leveraging forecasts, multi-hazard risk information and climate services to last-mile communities
● Bridging the gaps in risk and impact data to support impact-based forecasting, collecting and expanding data on interventions to build an evidence base for early actions
● Innovative solutions to address challenges in implementing forecast-based actions effectively, including the application of Artificial Intelligence, harnessing big data and earth observations.

Many water sectors are already having to cope with extreme weather events, climate variability and change. In this context, predictions on sub-seasonal and seasonal-to-decadal timescales (i.e., horizons ranging from months to a decade) are an essential part of hydrological forecasting. Applications of forecasts and the co-design of forecasting systems are essential for delivering impact to water sectors such as water supply, energy production and agriculture.

This session aims to cover research and operational advances in climate and hydro-meteorological forecasting, plus their implications for predicting water availability and servicing water sectors. It welcomes, without being restricted to, presentations on:

• Advances in sub-seasonal, seasonal and decadal hydrological predictions;
• Process-based, data-driven, machine learning and hybrid methods;
• Seamless forecasting techniques and applications;
• Hydro-climate forecasts and projections, including hydrological extremes, downscaling, bias correction, temporal disaggregation and spatial interpolation;
• Propagation of uncertainty through the forecasting chain;
• Impact-based assessments of forecasts for decision-making;
• Co-development of forecasts between scientists and service providers;
• Operational hydro-meteorological forecasting systems and hydro-climate services;
• Forecast verification, sensitivity analysis and tools; and
• Perspectives on forecast value for end users.

The session will bring together research scientists and operational managers in the fields of hydrology, meteorology and climate, with the aim of sharing experiences and initiating discussions on this momentous topic. We encourage presentations with impacts for water resources management, drinking water supply, transport, energy production, agriculture, disaster risk reduction, forestry, health, insurance, tourism and infrastructure.

One of the key issues in addressing flood-related disasters is the development of improved flood forecasting and early warning systems. With the advancements in hydro-meteorological measurement techniques through ground-based weather radar systems and satellite-based surrogate measurements in data scarce regions and data availability at different spatial and temporal scales, improved methods for forecasting with reasonable lead times can be developed. Advanced innovative methods and conceptual improvements in existing approaches are required to address the modeling and management of extreme floods' spatial and temporal complexity. The ensemble forecasting technique continues to be used for different lead time durations and for probabilistic flood forecasting. Different flood forecasting methods, including conceptually simple ones, are in use around the globe considering the complexity of the river basins, the cost of the development of the models, the lack of comprehensive hydro-meteorological monitoring networks, and other issues. One of the major factors of the cascading uncertainty through the hydrological models needs to be addressed in the probabilistic flood forecasting systems. This session aims to connect, identify, and publish the efforts of researchers globally to improve flood forecasting and issue early warnings ahead of catastrophic events. Research studies and case-study-specific studies dealing with the evaluation and verification of hydro-meteorological data, advanced forecasting methods, significant advances in ensemble forecasting techniques, and early warning systems in data-scarce and rich regions are appropriate for this session. The session also welcomes studies based on physics-based models and data-driven models.

In recent decades, there has been a growing focus on non-structural approaches, particularly early flood forecasting and warning systems, as effective means to mitigate the adverse impacts of floods. These systems have attracted attention for their ability to provide timely information to both citizens and authorities, enabling them to take necessary actions to safeguard their properties and infrastructure without the need for physical modifications or additional space. Real-time flood forecasting (RTFF) systems have gained popularity in early flood warning.
Data for RTFF can be sourced from various outlets, though sometimes access to these sources can be limited or challenging. RTFF necessitates the modeling of complex distributed systems with high spatial and temporal intricacies. This demands substantial computing resources and may leave limited time for timely early warnings. Significant breakthroughs have occurred in recent decades to address major challenges in the key stages of RTFF, including data collection and preparation, model development, performance assessment, and practical applications.
The objective of this session is to address challenges and advancements in the field by leveraging state-of-the-art techniques, new frameworks, equipment, software tools, hardware facilities, and the integration of existing methods with contemporary algorithms. We will also explore digital innovations and their applications in new pilot studies.
Specifically, this session will concentrate on the following research areas related to RTFF, with a focus on but not limited to:
● Hydrological data collection, analysis, imputation, assimilation and fusion taken from various data sources including ground stations, radar stations, remote sensing (aerial/satellite)
● RTFF modelling including physically/processed-based, conceptually-based, experimentally-based or data-driven modelling such as artificial Intelligence (AI), machine learning (ML)
● Application RTFF for flood alleviation or engagement with the public and authorities, such as early warning and early action systems, digital innovations such as digital twins (DT), or integrated with digital technologies such as augmented reality (AR) and virtual reality (VR).
● The broader implications of RTFF and early warning systems as soft engineering approaches, including their impact on flood risk management, insurance, capacity building, and community resilience.

Climate services have a well-recognised potential for empowering decision makers in taking climate-smart decisions, through the provision of climate-relevant information at sub-seasonal to seasonal scales, early warning of drought and water scarcity, and/or longer-term climate projections. Recent decades have seen significant advances that underpin the climate science data provided through such services, but despite these advances, crossing the last-mile in early warning proves to be challenging and barriers remain to actual uptake and use. These barriers include the lack of understanding of end-user needs and the options end-users have to respond; limited understanding of the decision-making processes of users, and a poor recognition of the local knowledge they hold and the role it can play in the provision and uptake of climate services.

Research shows, however, that more human-centred approaches and integration of local and traditional knowledges within climate services co-design and co-delivery can help establish services that are credible, salient and legitimate; leading to improved uptake and use. This is also recognised in recent initiatives such as the Early Warning for All launched recently by the United Nations.

This session addresses grounded research that advances the integration and combination of local and scientific knowledges in climate services, in particular in services that provide early warning to drought and water scarcity, heat waves, and advance information on water availability to support water resources management decisions across sectors such as water allocation, crop planning, reservoir operations (including hydropower) etc. We particularly encourage contributions that report action-based, multi-disciplinary research, involving multi-disciplinary researchers, and engagement with local stakeholders and communities. We encourage presentations that have had demonstrable impacts through improved uptake of advance warning, leading to better preparedness for climate extremes droughts and water scarcity, and better adaptation.

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 water cycle, especially in urban and regulated catchments, leading to further changes in the frequency, magnitude, and timing of hydroclimatic extremes in a warming climate. These modifications include reservoir and dam constructions, drainage systems, urban land expansion, urban infrastructure development, water abstraction, wastewater discharge, and associated management aspects and contingency plans.

Despite recent advances in hydrology research and technology developments in the Anthropocene, our understanding of human–water interactions in both large- and local-scale hydrologic systems remains elusive. This knowledge gap is mainly due to the complexity of human influences, limited and patchy records on human activities, and the inadequacy of conventional modelling approaches that are often designed for natural catchments assuming stationarity conditions. As a result, the accuracy and reliability of hydrological forecasting in these human-influenced catchments are significantly affected. Given the large populations potentially affected by water-related hazards in these areas, there is an urgent need for more focused attention and research.

This session will explore recent advances in hydrological forecasting (e.g. floods, droughts, moisture-driven landslides, and compound or cascading hydro-hazards) for urban and regulated catchments. We invite abstracts focusing on (but not limited to) the following topics:
• Developments and applications of advanced statistical, process-based, and machine learning models for forecasting hydroclimatic extremes in urban or regulated catchment
• Recent developments in data acquisition for capturing human activities (or proxy data), including in-situ measurements, remote sensing, paleoclimatic record, and social media, as well as hydrological dataset analytics and integration
• Novel quantitative approaches for human impacts (of any type) on the water cycle and hydrological processes
• Impact-based assessment of water-related risks, such as economic impacts, human health and safety, social and community impacts, and environmental impacts
• Uncertainty quantifications and risk assessments of singular and compound hydro-hazards under climate non-stationarity
• Improved visualization and effective communication methods designed for early warnings and short-to-long-range predictions of rare and ‘record-breaking' extreme events.

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. The session will feature state-of-the-art contributions to water and multisector resource system management solutions under uncertainty.

The global water crisis represents a critical and multifaceted challenge, intensified by the impacts of climate change, rapid population growth, and the unequal distribution of water resources. Addressing water management on a regional to global scale necessitates innovative, large-scale systems solutions that integrate advanced technologies, robust policy frameworks, and sustainable management practices. This session aims to examine state-of-the-art research and practical strategies for large-scale water management, emphasizing scalable solutions to mitigate issues related to water scarcity, quality, and accessibility. Key topics include multi-sectoral water impact assessments; behavioral modeling in water use; sustainable infrastructure development; and transboundary water governance, and multiscale modeling of interactions between water energy, food, and ecosystems. The session seeks to promote interdisciplinary dialogue, showcase effective case studies, and identify collaborative pathways among researchers to foster sustainable management of water resources for future generations.

Ensuring reliable water availability and access of acceptable quantity and quality in the face of increased urbanization, climate change, and economic instability remains one of the foremost challenges and priorities of the SADC Member States.
The United Nations Water Conference 2023 highlighted the need for concrete actions to boost integrated water resources management for achieving the Sustainable Development Goals and called for strategies to enhance cooperation among stakeholders. UN 2023 also identified Five accelerators towards SDGs and these included interventions in (1) Data and information (2) Capacity development (3) Governance, (4) Innovation and (5) Financing. Similarly, the fifth SADC Regional Strategic Action Plan (RSAP V, 2021-2025) on Integrated Water Resources Development and Management was developed through a regional consultative process and is meant to guide the management and development of regional water resources. Key themes identified under the, “Water Resource Management and Environment” focal area include, (i) assessment of surface and groundwater resources, (ii) operational rules for effective water resources management, (iii) impact of urbanization on water resources, (iv) water governance and institutional arrangements, (v) ecosystems, as well as (vi) water and land. This was informed in part by the SADC research agenda pillars for the water sector as well as the SADC 2050 vision.
In this session the status and water challenges in the SADC region linked to the key themes identified by the RSAP V will be presented and discussed. The session will evaluate, identify and highlight promising opportunities for science to accelerate progress in these areas going forward.
We aim to follow-up with a splinter meeting to collaborate on publishing a special issue on the status and challenges in water resources management in the SADC region.
More details of the timing and location of this splinter meeting will follow.

The management and utilization of water storages such as dams and reservoirs have played a central role throughout history in ensuring a steady water supply during dry periods, supporting various sectors including domestic, industrial, and agricultural needs. However, the increasing water demands due to population growth coupled with the ongoing climate extremes with their impacts on drought and precipitation patterns accentuate the crucial need for efficient and sustainable water reservoirs management. Projected global warming is expected to influence the operation and storage efficiency of water reservoirs (e.g., via intensified evaporative losses) posing serious risks to a wide range of stakeholders. Considering the intensity and frequency of recent climate extremes (drought, heatwaves, intensive precipitations), it is more important than ever to develop sustainable and effective water management as well as strategies that incorporate various environmental and socio-economic drivers and pressures affecting water reservoirs. This session solicits theoretical and experimental analyses that investigate managing both natural and human-made water reservoirs under different local and global change scenarios and identify the associated risks to sustainable water reservoirs management. The session aims to unite various contributions that present effective strategies, tools, and technologies to enhance sustainable management and implementation of freshwater storages. This includes, but not limited to, remote sensing methods, in situ measurements, AI-based approaches, and hydrological models for investigating present and future dynamics of freshwater availability, risk assessments, storage efficiency enhancement, and water allocation policies to devise the necessary action plans and appropriate adaptation schemes to cope with water scarcity in a warming climate.

In arid and semi-arid regions such as the Middle East, Caucasus, and Central Asia (MECCA), water scarcity is intensifying due to the degradation of transboundary aquifers and river flows, driven by climate change impacts like accelerated glacier melt and shifting rainfall patterns, as well as anthropogenic factors such as upstream water resource development and land-use changes. Environmental catastrophes such as the shrinking of the Aral Sea and Lake Urmia, the alarming decline of the Caspian Sea, and the diminishing flow of the Tigris and Euphrates rivers serve as critical examples of the consequences of unsustainable water management. These shifts have profound socioeconomic and environmental impacts, creating an urgent need for innovative and sustainable solutions.

As countries in the region confront the stark reality of shrinking water resources, this session will focus on scientifically grounded strategies for managing transboundary water systems. Emphasis will be placed on adaptive management frameworks and fostering cross-border collaboration among governmental, academic, and non-governmental stakeholders. By incorporating lessons learned from past environmental challenges, the session aims to help mitigate the risk of future crises, such as the potential desiccation of the Caspian Sea. Drawing on technical terminology, cutting-edge research, and real-world case studies, the session will offer practical, interdisciplinary approaches to mitigating water scarcity and enhancing regional water security in the face of climate change and human-induced pressures.

The science policy interface is key to addressing current and future scientific problems. It is not only a way to increase the impact of scientific output, but also a way to translate scientific results into actionable knowledge that supports evidence-based decision making and policy. For hydrological scientists, interactions with policy makers are also key to enhancing the way water-related research questions are formulated, and societal challenges are addressed to support realistic and feasible local solutions. With the ever-increasing pressures on water availability and the profound social, economic, ecological and political impacts, a deeper understanding of water security and resilience (both regarding droughts and floods) in the science policy context is needed. This can identify hydrological research priorities and improve knowledge transfer and translation to support adaptive EU and global policies that focus on water resilience in the face of climate extremes.

This session provides the opportunity for discussing and addressing avenues for 1) understanding the functioning of the many science and policy interfaces in hydrological sciences, 2) the role that research and operations must play in developing water resilience and 3) the impact adaptative polices and directives have on promoting water resilience locally or globally. Specifically, we also want to highlight the role of science in providing impartial scientific evidence-based guidelines for fostering ‘blue diplomacy” in transboundary river basin cooperation initiatives and underlining the need for interdisciplinary approaches to addressing water concerns in Europe and worldwide. Therefore, we welcome abstracts related to interdisciplinary science policy research to build water resilience, transboundary water research, and water diplomacy initiatives.

Water scarcity and management under uncertain future conditions represent significant global challenges that necessitate 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 water systems, but it introduces uncertainty regarding their long-term viability and integration into existing 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.

The science-policy-practice (SPP) nexus approach is considered optimal in the sustainable management and governance of water resources, which lies at the heart of the global development. Whilst the science-policy interaction has received considerable attention, the practice component of this nexus remains to be comprehensively promoted for both improving operational hydrology services and achieving science-informed policies.

Operational hydrology as part of practice is defined by the World Meteorological Organization (WMO) as “the real-time and regular measurement, collection, processing, archiving and distribution of hydrological, hydrometeorological and cryospheric data, and the generation of analyses, models, forecasts and warnings which inform water resources management and support water-related decisions, across a spectrum of temporal and spatial scales'' (WMO, 2019). The operationalization of research for hydrological services is not straightforward.

Whilst applied hydrology research is of direct relevance to many professionals - such as national hydromet agencies and catchment managers - uptake is still limited. Development and sharing of methods/tools by the scientific community is necessary for translating scientific information into a format facilitating education, decisionmaking and policy formulation (UNESCO IHP IX, 2022-2029). Making hydrology research actionable should be a priority strategy in the design of knowledge translation mechanisms. In the context of SPP, this requires alignment of needs/expectations and an understanding of the frameworks that different stakeholders must work within, and the agendas/ legal constraints contemporary and salient to them and their funders.

Liaising with stakeholders, policy-makers, and society is needed not only to turn research into impactful action but also to improve research outcomes by capturing issues that cannot be understood via disciplinary lenses. It is necessary to create the interdisciplinary knowledge needed to address the questions faced by decision-makers and all the societal stakeholders.

For this session, we welcome contributions on interdisciplinary collaborations and existing hydrology initiatives, organizations, and networks that offer modalities and frameworks aimed at connecting typically isolated stakeholders of research and improving hydrological research-services interface on various scales and directions.

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. Its interdisciplinary nature encompasses (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. Here, 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.

Access to safe and affordable water, resilience to climate risks, and participation in decision-making are three pillars to achieve equity and justice in water systems. Factors such as environmental degradation, institutional failures, deficient supply systems, and socio-economic disparities can drive inequitable water access especially for marginalized and under-resourced communities in both urban and rural areas. Climate change further intensifies these challenges by increasing frequency and intensity of extreme events and straining water infrastructure. Addressing these disparities necessitates reimagining water systems and the management of water resources to ensure outcomes that are equitable, inclusive, and resilient to climate change and other anthropogenic pressures. In this session, we invite contributions that advance community-driven water research, computational methods to support just decision-making, resilient and adaptive water planning and management, and equitable water governance. Together, we aim to explore actionable pathways towards more equitable and just water systems.

This session welcomes abstracts that consider how to observe, analyse and model feedbacks of people and water, and the effects of social and environmental changes on hydrological systems. It is organised by the 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.
Examples of relevant topics include:
• Observations of human impacts on, and responses to, hydrological change
• Interactions of communities with local water resources
• Hydrological models that include anthropogenic effects
• Interdisciplinary qualitive and quantitative methods including theoretical models to isolate, conceptualize and/or simulate feedbacks in human water systems
• Creation of databases describing hydrology in human-impacted systems
• Data analysis and comparisons of human-water systems around the globe and especially in the global south
• Human interactions with hydrological extremes, i.e. floods, droughts and water scarcity
• The role of gender, age, disability status, primary language, nationality/refugee status and cultural background in the impacts of hydrological extremes, risk perception, and during/after crises and emergencies

Water sustains societies, economies, and ecosystem services locally and globally. Competition and conflict over access to and use of freshwater resources in many regions around the world is increasing as a result of changes in water demand, coupled with shifts in water availability due to climate change and variability. To address these challenges, integrative approaches to water management and policy are required to balance and manage trade-offs between social, economic, and environmental uses of water. In addition, there is an emerging need for adaptive and flexible solutions capable of updating decisions to changing climatic and socio-economic conditions to enhance the resilience of water systems. This session will provide 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 to the session that: (i) identify knowledge gaps and improvements to understanding about the critical interconnections, feedbacks, and risks between water system components, (ii) highlight development of new methods or tools for evaluating and monitoring trade-offs and performance in water allocation and management between different users and sectors, (iii) evaluate alternative technological, policy, and/or governance interventions to address the water-food-energy-environment nexus in different locations and at various scales (local, regional, and/or global), and (iv) advance methods to evaluate risks to water systems and identify solutions to enhance their 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 nexus.

Climate change presents one of the most pressing global challenges, with far-reaching implications for both natural and human systems. Among the myriad consequences of climate change, the rise in climate extreme events has been well-documented through observational and modelling studies. These extremes, ranging from heavy precipitation and floods to heatwaves, wildfires, and droughts, exert profound and often devastating impacts on agriculture and the society. In this context, understanding the intricate connectivity between agricultural and hydrological systems under the influence of climate change has emerged as a critical research imperative, and necessitates a multidisciplinary approach.

Recent advancements in remote sensing, machine learning, and the development of process-based models offer immense potential for in-depth investigations into agriculture and hydrological interactions in a changing climate. This session aims to solicit and showcase research contributions that employ diverse methodologies, particularly Earth Observations, machine learning approaches, and numerical/statistical models, to monitor, simulate, and predict the interaction and feedback between agricultural and hydrological systems, spanning various spatiotemporal scales.

We invite researchers to engage in this session and contribute to the collective understanding of how climate change impacts the intricate relationship between agricultural and hydrological systems. Topics of interest include, but are not limited to:

1. Observational insights: Present observational evidence and case studies that shed light on observed climate extremes, their effects on agricultural systems, and hydrological responses.
2. Machine learning applications: Innovative applications of machine learning algorithms to analyze and predict the impacts of climate extremes on agriculture and hydrology.
3. Numerical and Statistical Modeling: Utilize numerical and statistical models to simulate and project future scenarios of climate-induced changes in agricultural and hydrological systems.
4. Scaling Effects: Investigate the interconnectedness of agricultural and hydrological systems across various spatial and temporal scales, elucidating regional and global implications.
5. Adaptation and resilience: Discuss strategies for adapting agriculture and hydrology to climate extremes, emphasizing the importance of building resilience in these systems.

Land and water are mutually intertwined and each decision on land is also impacting water and water-related ecological processes. Land use and land cover (LULC) can alter hydrological processes and ecosystem dynamics and thereby affect critical biosphere functions, such as food production. These changes can emerge directly from anthropogenic interventions, or indirectly as the result of climate change.

Novel approaches are needed to assess the impact of LULC changes on the hydrological cycle (e.g. streamflow, groundwater quantity and quality, evaporation and transpiration, soil moisture, and rainfall interception) and its associated water-related ecosystem services (WES), including primarily the production of food. This includes the analysis of non-local and non-linear effects, incorporating socio-ecological systems, and identifying the feedback between land and water systems. In light of these interlinkages, new perspectives and interdisciplinary approaches, such as ecohydrology, agro-hydrology as well as socio-hydrology, are needed to inform effective and equitable water resource management.

This session welcomes studies that explore the impacts of LULC changes on all water resources, hydrological processes, and associated WES, primarily food production. More specifically, we welcome studies including, but not limited to:

• Advances in the quantification of hydrological impacts of LULC changes through agro- eco- and socio-hydrological modelling or the analysis of experimental data
• Advances in multi- and interdisciplinary methodologies for the assessment of the water-land nexus, including considerations on food and water security
• Analysis and evaluation of policy interventions to manage the land-water nexus, such as ecological restoration schemes and nature-based solutions, with respect to their effectiveness and feasibility
• Socio-hydrological and hydro-social approaches dealing with land, water, and ecosystem management, aiming also to highlight feedback loops between social and bio-geophysical dynamics
• Disentanglement of LULC and climate change impacts on water resources (surface and groundwater, green water, atmospheric water) hydrological processes, and associated WES.

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, 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/

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 of GI, Sustainable Drainage Systems (SuDS), Low Impact Developments (LIDs) or Nature-based Solutions (NbS), which provide an evidence base for integration within a wider hazard management system;

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

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

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

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

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

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

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

Urban watersheds face unique challenges amidst the need of water to support society as well as nature. The compounding effects of high percentages of impervious surface areas, degraded water quality, extreme heat and increased risk of flooding call for more sustainable and equitable urban water management and an improved understanding of urban watershed behavior. This session invites all urban environmental science research, with a particular focus on urban hydrology and urban water challenges. We welcome a wide breadth of studies on urban hydrology characterization and catchment functioning, runoff and pollution in urban watersheds, flood and drought risks in urban or urbanized regions, compound hazards and risk assessment methodologies, green-blue infrastructure and storm water management solutions, as well as community engagement and climate adaptation strategies in urban areas.

Rapid urbanization and human-induced changes to natural river systems and riverine ecosystems make cities more vulnerable to extreme flooding. Balancing development with urban river health and the safety of communities becomes a growing challenge with the expansion of urban areas.
This session explores advancements in flood forecasting for extreme events, focusing on real-time data assimilation, changes in riverine ecosystems, and predictive technologies. These tools are critical for predicting flood risks and improving city-wide preparedness. The emphasis will be on real-time flood alert technologies, sustainable urban solutions, including nature-based interventions like sustainable drainage systems and river restoration projects, which mitigate flood risks while preserving urban river health and contributing to long-term environmental sustainability. The session will also encompass a comprehensive understanding of real-time data acquisition methods, machine learning and deep learning-based predictive approaches, and IoT-based communication systems.
Additionally, emphasis will be placed on the significance of effective communication among city planners, governments, experts, and communities to ensure timely disaster preparedness and response. Effective and comprehensible communication during early warnings is crucial for safeguarding lives and livelihoods.
Through this session, participants will gain a deeper understanding of how to build flood-resilient cities, safeguard urban rivers, and ensure inclusive participation in flood management and urban development strategies.

Water utilities and municipalities are embracing technological innovation at different paces to address the challenges and uncertainties posed by urbanization, climate and demographic changes. The progressive transformation of urban water infrastructure and the adoption of digital solutions are opening new opportunities for the design, planning, and management of urban water networks and human-water systems across scales, in pursuit of sustainability and resilience. The “digital water” revolution is enhancing the interconnection between urban water systems (drinking water, wastewater, urban drainage) and other critical infrastructure and ecosystems (e.g., energy grids, transportation networks). This growing interconnection calls for new approaches that take into account the complexity of these integrated systems.
This session aims to provide an active forum to discuss and exchange knowledge on state-of-the-art and emerging tools, frameworks, and methodologies for planning and management of modern urban water infrastructure, with a particular focus on digitalization and/or interconnections with other systems, looking at the bigger picture. Topics and applications may cover any area of urban water network analysis, modeling, and management, including intelligent sensors and advanced metering, digital twins, asset management, decision making, novel applications of IoT, and challenges to their implementation or risk of lock-in of rigid system designs. Methods and approaches may also include big-data analytics and information retrieval, data-driven behavioral analysis, graph theory, ontologies and artificial intelligence for water applications (including large language models and physics-informed machine learning), descriptive and predictive models of, e.g., water demand, sewer system flow/flood extent, experimental approaches to demand management, water demand and supply optimization, energy recovery from urban water networks, real-time control of urban drainage systems, anomaly identification in hydraulic and water quality sensor data (e.g., for leak detection, identification of contamination events). Investigations on interconnected systems could explore emerging areas such as cyber-physical security of urban water systems (i.e., communication infrastructure), combined reliability and assessment studies on urban metabolism, or minimization of flood impacts on urban networks and energy usage optimization.

We invite presentations concerning remote sensing of soil moisture, field experiments, data assimilation, Cal/Val activities and fiducial reference measurements (FRMs).
Remote sensing has made tremendous progress to provide robust estimates of soil moisture at different depths and scales. Field or aircraft experiments have been organised to improve our understanding of active and passive microwave soil moisture sensing, including the effects of soil roughness, vegetation, spatial heterogeneities, and topography. At global scale, instruments such as SMMR (1978-1987), AMSR (2002-), ERS/SCAT (1992-2000) provided information on surface soil moisture. Current L-band sensors such as SMOS (2009-) and SMAP (2015-), and active C-band observations with the Metop/ASCAT series (2006-) and Sentinel-1, also enable an accurate quantification of the soil moisture. Operational programmes like Copernicus and novel developments will further enhance our capabilities to monitor soil moisture from agricultural to climate scales. Furthermore, research has put a new focus on establishing rigorous guidelines for the installation, calibration, operation, maintenance, and use of in situ soil moisture measurements using metrological practices, as well as on the development of advanced quality control procedures for in situ soil moisture measurement networks to obtain so-called fiducial reference measurements (FRMs).

We encourage submissions related to soil moisture remote sensing, including:
- Field experiments and theoretical advances in microwave modelling
- High spatial resolution soil moisture estimation based on, e.g., Sentinel observations, GNSS reflections, or using novel downscaling methods.
- Preparation of future missions including passive L-band high resolution concepts, CIMR, Metop-SG/SCA, NISAR....
- Root zone soil moisture retrieval and soil moisture data assimilation in land surface models, hydrological models and in Numerical Weather Prediction models.
- Evaluation and trend analysis of soil moisture climate data records.
- Inter-comparison and inter-validation between land surface models, remote sensing approaches and in-situ validation networks.
- Uncertainty characterization across scales and progress towards traceable uncertainty budgets in particular for data assimilation
- Soil moisture reference networks, especially the establishment of FRMs.
- Application of satellite soil moisture products for improving hydrological and other applications.

This session will focus on using remote sensing to advance evapotranspiration (ET) quantification across a range of climates and environments. We invite contributions that explore how remote sensing can enhance ET assessments and predictions in diverse settings such as agriculture, riparian zones, urban areas, and forests. By applying these methods from regional to global scales, we aim to tackle the challenges of ET estimation and improve our understanding of water dynamics in various landscapes.

With the increased attention of society to climate change, drought and flood early warning systems, ecosystem monitoring, and biodiversity conservation, and reaching a sustainable future, the demand for estimating, modelling, mapping, and forecasting evapotranspiration (ET) has expanded. New techniques such as artificial intelligence (AI) and other techniques, such as data fusion, sharpening algorithms, and the combination of physical- and process-based models with empirical/statistical methods and machine learning are cutting-edge. These techniques and the variety of space/airborne sensors introduce new horizons to quantify ET at different scales over various land covers. Cloud computing platforms provide scientists and researchers with the pivotal tool, data, and computing resources to model and analyze hydrological parameters like ET while offering scalability, efficiency, and collaboration opportunities. Remote sensing (RS) of ET supports evidence-based decision-making, helps in addressing water-related challenges, contributes to sustainable water management practices, and better informs managers, end-users, and the community.

In our session of RS of ET, we welcome your research findings, commentary pieces and debates on:
a. recent developments in RS of ET
b. application of AI, cloud computing and technology advancement;
c. fusion of RS, modelling and ground-based methods;
d. validation, calibration and upscaling challenges and improvements;
e. future directions in RS of ET.

Snow constitutes a freshwater resource for over a billion people worldwide. A high percentage of this water resource mainly comes from seasonal snow. The ongoing warming poses a significant risk to snow water storages, potentially leading to a drastic reduction in water supply and causing adverse effects on the ecosystems.
Therefore, understanding seasonal snow dynamics, possible changes, and implications have become crucial for water resources management.

Remote sensing technology plays a crucial role in monitoring snow properties and their hydrological implications across spatial and temporal scales, allowing for a better understanding of snow dynamics (e.g., the interaction of snow with small-scale, quick snow changes within a day, rain on snow events, snow-vegetation interaction).

This session focuses on studies linking the use of remote sensing of seasonal snow to hydrological applications to: (i) quantify snow characteristics (e.g., SWE, snow grain size, albedo, pollution load, snow cover area, snow depth and snow density), (ii) understand and model snow-related processes and dynamics (snowfall, melting, evaporation, wind redistribution and sublimation), (iii) assess snow hydrological impacts and snow environmental effects. Works including technique and data from different technologies (time-lapse imagery, laser scanners, radar, optical photography, thermal and hyperspectral technologies, or other new applications) across spatial (from the plot to the global) and temporal (from instantaneous to multiyear) scales are welcome.

This session focuses on the hydrogeodetic measurement of water bodies such as rivers, lakes, floodplains and wetlands, groundwater and soil. The measurements relate to estimating water levels, extent, storage and discharge of water bodies through the combined use of remote sensing and in situ measurements and their assimilation in hydrodynamic models.

Monitoring these resources plays a key role in assessing water resources, understanding water dynamics, characterising and mitigating water-related risks and enabling integrated management of water resources and aquatic ecosystems. While in situ measurement networks play a central role in the monitoring effort, remote sensing techniques provide near real-time measurements and long homogeneous time series to study the impact of climate change 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 and 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 still challenging with available spaceborne techniques. Interferometric Synthetic Aperture Radar (InSAR) is also commonly used to understand wetland connectivity, floodplain dynamics and surface water level changes, with more complex stacking processes to study the relationship between ground deformation and changes in groundwater, permafrost or soil moisture.

Traditional instruments contribute to long-term water level monitoring and provide baseline databases. Scientific applications of more complex technologies like Synthetic Aperture Radar (SAR) altimetry on CryoSat-2, Sentinel-3A/B and Sentinel-6MF missions are maturing, including the Fully-Focused SAR technique offering very-high along-track resolution. The SWOT mission, recently lauched and commissioned, now opens up many new hydrology-related opportunities. We also welcome submissions of pre-launch studies for CRISTAL, Sentinel-3C/3D/3NG-Topography, Sentinel-6NG, MAGIC/NGGM and and other proposed missions such as Guanlan, HY-2 and SmallSat constellations such as SMASH, and covering forecasting.

The socio-economic impacts associated with floods are increasing. Floods represent the most frequent and most impacting, in terms of the number of people affected, among the weather-related disasters: nearly 0.8 billion people were affected by inundations in the last decade, while the overall economic damage is estimated to be more than $300 billion.
In this context, remote sensing represents a valuable source of data and observations that may alleviate the decline in field surveys and gauging stations, especially in remote areas and developing countries. The implementation of remotely-sensed variables (such as digital elevation model, river width, flood extent, water level, flow velocities, land cover, etc.) in hydraulic modelling promises to considerably improve our process understanding and prediction. During the last decades, an increasing amount of research has been undertaken to better exploit the potential of current and future satellite observations, from both government-funded and commercial missions, as well as many datasets from airborne sensors carried on airplanes and drones. In particular, in recent years, the scientific community has shown how remotely sensed variables have the potential to play a key role in the calibration and validation of hydraulic models, as well as provide a breakthrough in real-time flood monitoring applications. With the proliferation of open data and models in Earth observation with higher data volumes than ever before, combined with the exponential growth in deep learning, this progress is expected to rapidly increase.
We invite presentations related to flood monitoring and mapping through remotely sensed data including but not limited to:
- Remote sensing data for flood hazard and risk mapping, including commercial satellite missions as well as airborne sensors (aircraft and drones);
- Remote sensing techniques to monitor flood dynamics;
- The use of remotely sensed data for the calibration, or validation, of hydrological or hydraulic models;
- Data assimilation of remotely sensed data into hydrological and hydraulic models;
- Improvement of river discretization and monitoring based on Earth observations;
- River flow estimation from remote sensing;
- Deep learning based flood monitoring or prediction
Early career and underrepresented scientists are particularly encouraged to participate.

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 potential and continuous development of advanced sensors (e.g., new satellite missions) and retrieval methods (e.g., innovative machine learning, data assimilation and data merging 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.

With the proliferation and wide accessibility of remotely sensed information, data from missions such as Landsat, Sentinel, and MODIS are being increasingly used to develop a better understanding of hydrological processes on the earth’s surface. Acquiring 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 and without a thorough critical examination of their applicability and limitations. In-situ data, though often less readily available and more eclectic, provide a valuable layer of information to act as a benchmark against methods relying solely on remotely sensed data.
This session aims to highlight innovative approaches to harnessing a synthesis of remotely sensed and in-situ data to better understand processes related to hydrology at regional and local scales in a variety of environments. We welcome contributions that focus on combining remote sensing and in-situ information and critically engage with this intersection with relation to:
Processes such as evapotranspiration, infiltration, (Monsoon) inundations, water abstraction for agricultural use
Hydrological extremes such as floods and droughts
Coping with a sparsity of in-situ data in poorly gauged and ungauged basins
Developing novel methods of gathering in-situ benchmark data to combine with remotely sensed approaches
Reviewing recent synthesised advances of RS application in hydrology, in natural and anthropised ecosystems

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 (EEA, 2009; Zucaro 2014). North Africa region has the lowest per-capita freshwater resource availability among all Regions of the world (FAO, 2018).
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.

Remote sensing products have a high potential to contribute to monitoring and modelling of water resources. Nevertheless, their use by water managers is still limited due to lack of quality, resolution, trust, accessibility, or experience.
In this session, we look for new developments that support the use of remote sensing data for water management applications from local to global scales. We are looking for research to increase the quality of remote sensing products, such as higher spatial and/or temporal resolution mapping of land use and/or agricultural practices or improved assessments of river discharge, lake and reservoir volumes, groundwater resources, drought monitoring/modelling and its impact on water-stressed vegetation, as well as on irrigation volumes monitoring and modelling. We are interested in quality assessment of remote sensing products through uncertainty analysis or evaluations using alternative sources of data. We also welcome contributions using a combination of different techniques (physically based models or artificial intelligence techniques) or a combination of different sources of data (remote sensing and in situ) and different imagery types (satellite, airborne, drone). Finally, we wish to attract presentations on developments of user-friendly platforms (as open as possible), providing smooth access to remote sensing data for water applications.
We are particularly interested in applications of remote sensing to determine the human water interactions and the climate change impacts on the whole water cycle (including the inland and coastal links).

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.
- 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.

Hydroclimatic conditions and availability of water resources in space and time constitute important factors for maintaining adequate food supply, the quality of the environment, and the welfare of citizens and inhabitants, in the context of a post-pandemic sustainable growth and economic development. 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.)

Scientists are facing several challenges when applying climate models for hydrological variables. Indeed, a gap exists between what is provided by climate scenarios and what is needed and useful for technical hydrological studies. In order to reduce this gap and enhance the assessment of climate change impacts, we need to improve our understanding, knowledge and model representations of the interactions between climate drivers and hydrological processes at regional and local scales. This is essential to outline forecasts and assess the risk associated with extreme events, where uncertainty, probabilistic approaches ad prediction scenarios should be properly defined.

This session particularly welcomes, but is not limited to, contributions on:
- Advanced techniques to simulate and predict hydrological processes and water resources, with emphasis on stochastic and hybrid methods.
- Advanced techniques to simulate and predict hydroclimatic extreme events including compound extreme events (e.g. heatwaves, floods and droughts).
- Holistic approaches to generate future water resources scenarios integrating also anthropogenic and environmental perspectives.
- Hydroclimatic change attribution studies using probabilistic approaches and novel causality frameworks with uncertainty assessment.
- Evaluation of climate models performance at regional and local scales using observational data

This session is supported by the International Association of Hydrological Sciences (IAHS), the World Meteorological Organization, the National Recovery Resilience Plan RETURN Foundation of Italy, and it is also related to the scientific decade 2023–2032 of IAHS, “HELPING”.

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

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

Significant empirical and theoretical advancements have revealed the departure of hydrometeorological processes from classical statistical models, highlighting the scaling behavior of their variables, especially extremes, across state, space, and time. These extremes, along with the general statistics of hydrometeorological processes, are crucial inputs for hydrological applications, which have increasing importance in the (re)insurance industry. Among the most common applications, catastrophe models are developed to manage risk accumulation; disaster response is used to prepare (re)insurers financially after major events; Real Disaster Scenarios are built to stress-test (re)insurers exposure both in the present-day and future climate.
For instance, in the context of a flood risk model, estimating design rainfall not only involves determining the absolute rainfall amount for a specific return period but also requires understanding the intra-event rainfall distribution, spatial extension, and rainfall intensities at neighboring stations. When these details are underestimated, it can easily turn into a poor risk assessment and weaker financial protection. Additionally, connections between hydrometeorological extremes and climatic oscillations, such as NAO or ENSO, and their evolution in a changing climate, provide insights for long-term risk management in the re-insurance sector, as required for regulatory purposes.
The integration of supporting information and the application of advanced AI approaches offer as well unprecedented opportunities to enhance these estimates. This session invites submissions, among others, on the following topics:
- Coupling stochastic approaches with deterministic hydrometeorological predictions to better represent predictive uncertainty.
- Developing robust statistics under non-stationary conditions for design purposes.
- Parsimonious models of hydrometeorological extremes across various spatial and temporal scales for risk analysis and hazard prediction.
- Improving the reliable estimation of extremes with high return periods, considering physical constraints.
- Linking underlying physics and hydroclimatic indices with the stochastics of hydrometeorological extremes.
- Exploring supporting data sets for additional stochastic information and utilizing novel AI and machine learning approaches.
- Applications carried out jointly by the (re)insurance industry and research institutions.

Hydroclimatic extremes such as floods, droughts, storms, or heatwaves often affect large regions and can cluster in time, therefore causing large socio-economic damages. Hazard and risk assessments, aiming at reducing the negative consequences of such extreme events, are often performed with a focus on one location despite the spatially compounding nature of extreme events. Also, clustering of extremes in time is often neglected, with potentially severe underestimation of hazard. While spatial-temporal extremes receive a lot of attention by the media, it remains scientifically and technically challenging to assess their risk by modelling approaches. Key challenges in advancing our understanding of spatio-temporal extremes and in developing new modeling approaches include: the definition of multivariate events; the dealing with large dimensions; the quantification of spatial and temporal dependence, together with the introduction of flexible dependence structures; the identification of potential drivers for spatio-temporal dependence; the estimation of occurrence probabilities, and the linking of different spatial and temporal scales. This session invites contributions which help to better understand processes governing spatio-temporal extremes and/or propose new ways of describing and modeling compounding events at different scales.

Traditionally, hydrologists focus on the partitioning of precipitation water on the surface, into evaporation and runoff, with these fluxes being the input to their hydrological models. However, more than half of the evaporation globally comes back as precipitation on land, ignoring an important feedback of the water cycle if the previous focus applied. Land-use and water-use changes, as well as climate variability and change alter, not only, the partitioning of water but also the atmospheric input of water as precipitation, related with this feedback, 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.

Typically, studies in this session are applied studies using 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 sources of data for atmospheric hydrology and implications for inter-comparison and meta-analysis. For example, observations networks, isotopic studies, conceptual models, Budyko-based hydro climatological assessments, back-trajectories, reanalysis and fully coupled Earth system model simulations.

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.

Dissolution, precipitation and chemical reactions between infiltrating fluid and the rock matrix alter the composition and structure of the rock, either creating or destroying flow paths. Strong, nonlinear couplings between the chemical reactions at mineral surfaces and fluid motion in the pores often lead to the formation of large-scale patterns: networks of caves and sinkholes in karst areas, wormholes induced by the acidization of petroleum wells, porous channels created as magma rises through peridotite rocks. Dissolution and precipitation processes are also relevant in many industrial applications: carbon storage or mineralization, oil and gas recovery, sustaining fluid circulation in geothermal systems, the long-term geochemical evolution of host rock in nuclear waste repositories or mitigating the spread of contaminants in groundwater.

With the advent of modern experimental techniques, these processes can now be studied at the microscale, with a direct visualization of the evolving pore geometry, allowing exploration of the coupling between the pore-scale processes and macroscopic patterns. On the other hand, increased computational power and algorithmic improvements now make it possible to simulate laboratory-scale flows while still resolving the flow and transport processes at the pore scale.

We invite contributions that seek a deeper understanding of reactive flow processes through interdisciplinary work combining experiments or field observations with theoretical or computational modeling. We seek submissions covering a wide range of spatial and temporal scales: from table-top experiments and pore-scale numerical models to the hydrological and geomorphological modelling at the field scale.

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.

With the recognition that per- and polyfluoroalkyl substances (PFAS) and other emerging chemicals contaminate the subsurface and pose health risks, significant progress has been made through laboratory, field, and modeling research. This session invites papers on recent advancements that enhance models, improve site characterization, and address new challenges in meeting regulatory goals and policy development. Contributions to traditional contaminants are also welcome to benefit from lessons learned that will be of use to PFAS and other emerging contaminants.

Recent research on PFAS has raised concerns and led to stricter regulation in many countries. PFAS combines aqueous mobility, extreme recalcitrance and adverse health effects at very low concentrations which requires immediate actions to reduce their release and spreading, better understand their transport and associated risks, and remove them from the environment. The unique properties of PFAS also pose many additional challenges for groundwater management, risk assessment and remediation. Many processes in both the groundwater and vadose zones need to be better understood and there is an urgent need for improved remediation and mitigation methods.

PFAS have produced additional challenges to our basic knowledge and models of solute fate and transport in the subsurface. The problem of transport of dissolved chemicals in vadose zone soils and groundwater has previously been extensively studied in applications of soil physics and hazardous waste chemicals contaminating groundwater. However, most contaminant transport studies and models focus on single solutes, with all solutes assumed to behave, for the most part, independently (i.e., the dilute solution approximation). Recent research has studied the basic processes of retention and transformation of PFASs in unsaturated and saturated soils under much more complex conditions of flow conditions where water dynamics determine the rates and types, not just the transformation. In upscaling this knowledge from laboratory batch and column testing conducted under idealized homogeneous soil conditions, it is required to understand the behavior under conditions of natural heterogeneities and multi-dimensional flow. This session will have particular focus on complex contaminant transport phenomena and their upscaling from the laboratory to real field sites.

Understanding ecosystems and geoscience at the relevant scales is crucial to push scientific frontiers and develop new hypothesis. The last three decades and alongside with the technological progress, analytical and experimental settings were more and more fine tuned to gain a better understanding of natural processes within and across all earth science disciplines. New insights were gained on a multitude of geosphere interactions. Hereby the small-scale interaction plays an important role in answering fundamental questions in i.e., understanding transport phenomena and governing mechanisms of different physical and chemical processes in porous media, enhance understanding of organic matter dynamics in soil systems or study transient processes between roots, minerals and microbes. Additionally, in recent years microfluidic chip applications have evolved towards in-situ sensing -or environmental monitoring platforms for contaminants, nutrients or microorganisms.
Micro engineered systems such as porous media models, microfluidic chips or 3D printed micro reactors bare the great potential to simulate less accessible environments, particularly at the relevant reactive scale. The full potential in various branches of natural sciences is yet to be explored.
Therefore, this session aims to collect and connect various disciplines of natural sciences who make use of microfluidics for process understanding. But moreover, to inspire each other and create new innovative experimental setups for their own applications.
We encourage contributions focusing on the following applications of microfluidic chips:
• understand microbial and fungal dynamics in soil analogs
• study contaminant behavior in soils and groundwater aquifers at the relevant scale
• microbial dynamics at the soil/air interface
• AI- suported image analysis to enhance subsurface process understanding of microbe and contaminant dynamics

Redox-sensitive multi-contamination scenarios in freshwater systems present unique challenges, particularly when contaminants require simultaneous but opposite redox conditions for effective remediation. This session focuses on the complexities and innovative solutions for managing co-contamination where one contaminant requires oxidation while another requires reduction—a scenario that represents one of the most challenging tasks in environmental remediation. Topics of interest include:

• Mechanistic insights into the simultaneous oxidation-reduction (redox) processes required for the effective treatment of co-contaminated freshwater systems.
• Advanced strategies for spatial or sequential redox manipulation to manage contaminants with conflicting redox requirements, such as the simultaneous reduction of nitrates and oxidation of organic contaminants or heavy metals.
• Novel materials and technologies (e.g., redox-active media, bioreactors, and nanomaterials) designed to achieve controlled redox environments for selective contaminant removal.
• Integrated modeling and monitoring approaches to predict and manage the complex interactions between redox processes and contaminant behaviour.
• Case studies showcasing real-world applications and the challenges faced in designing and implementing such complex remediation strategies.
This session seeks to engage researchers, practitioners, and policymakers in discussions on advancing the science and technology of redox-sensitive co-contamination management. Join us to explore novel approaches, share experiences, and collaborate on solutions for one of the most difficult tasks in environmental remediation.

This session combines contributions on recent developments in subsurface hydrology; theoretical approaches and experimental work will be discussed to provide reliable insights for groundwater protection and site remediation techniques.

Much effort has been put into understanding transport processes in recent years because of their practical relevance in determining the fate of contaminants in surface and subsurface waters that may affect human health and the environment. Correct quantification of transport processes is challenging and reflects the complexity of flow paths and physical processes in aquifers, as well as the heterogeneity of . It strongly influences predicted contaminant dispersion and plume properties and is fundamental for assessing the effectiveness of remediation strategies. Further efforts are now needed to apply these new concepts in practice for contamination prevention, vulnerability assessment and risk management.
The aim of this session is to discuss the latest theoretical and practical developments in transport theories and how they can be applied to the problems of aquifer characterisation, transport dynamics and remediation techniques.

Our contributions will address the following questions
- What are the recent improvements in appropriate methods to characterise the relevant aquifer properties for comprehensive modelling of contamination?
- What are the recent improvements in transport measurement techniques?
- What are the most appropriate approaches for the practical application of theoretical advances in groundwater transport modelling?
- How can we assess the most appropriate remediation strategy and predict its effectiveness?

Case studies and multidisciplinary approaches are encouraged.

The session is co-sponsored by the Groundwater Commission of the IAHS.

Self-potential (SP) is a non-invasive geophysical method used to map the natural electrical potential/field of the earth's surface. It allows to image and monitor fluid flow as well as any biotic or abiotic process out of thermodynamic equilibrium in the subsurface of the Earth able to generate an electrical current.
In this session, we invite submissions on the applications of self-potential method in hydrogeophysics including applications related to alluvial, and coastal aquifers; soil contamination; agriculture; fault zones; landslides; mining exploration; hydrothermal-geothermal systems; and volcanology. We encourage as well, talks or posters related to innovative laboratory experiments, field survey methods/methodologies, and advancements in theoretical and numerical modeling of this method. We also invite the use of a combination of coupled and joint approaches of self-potential signals in order to provide quantitative constraints on various hydrological and biochemical processes.

Groundwater flow and pollutant transport modeling has developed into a vital tool for the analysis of aquifers at different scales, from the pore to the global scales. Numerous applications employ modelling, such as risk assessment, water resource management, decision support systems, and remediation activity guidance. The hydrogeochemical and biological processes affecting flow and transport in heterogeneous porous media are extremely complex, as numerous studies have demonstrated. Since these processes frequently depend on one another, coupled flow and solutes transport modeling is essential.
The objective of this session is to discuss the state-of-the-art and future directions in groundwater flow modeling and simulation of solutes fate and transport in the saturated zone. It provides a special opportunity to promote inter-disciplinary studies and the sharing of knowledge and experiences related to analytical and numerical, physics-based approaches.

In a context of societal development and increasing demand for natural resources, human needs and environmental impacts must be considered together in order to sustainably manage these resources, especially with regard to groundwater resources. The issues become more challenging to solve considering their uneven and complex distribution. Sustainable groundwater resource management involves adopting integrated approaches that take into consideration interconnections among the different components of the hydrological cycle and understanding groundwater flow systems through the identification of governing processes and conditions from the local to regional and basin-scales, transcending administrative boundaries. This means considering not only the availability and quality of water resources, but also ensuring the preservation of related ecosystems. Moreover, the impacts on groundwater resources, ecosystems and societies due to ongoing climate change should also be considered.
The objective of this session is to gather case studies and scientific contributions connected to sustainable management of groundwater and its protection from degradation and deterioration, e.g., due to over-exploitation, competition for water resources, natural or anthropogenic contamination, and climate change. Contributions are invited, but not limited to, the following subjects: (i) the use of environmental tracers (chemical species and isotopes) for investigating natural processes and human impacts on water resources, (ii) the assessment of hydrogeological budgets for the evaluation of water availability, and (iii) methods for characterizing groundwater flow systems, and preventing, managing and mitigating harmful environmental impacts related to groundwater, as well as (iv) identifying major existing challenges and critical issues.
The Regional Groundwater Flow Commission (RGFC) of the International Association of Hydrogeologists (IAH) is sponsoring the session.

Data-driven models are increasingly applied to solve groundwater problems, such as predicting groundwater levels or groundwater quality parameters. These models often rely less on detailed knowledge of subsurface processes but rather on empirical relationships of available data sets and the variable of interest. Observational data are typically scarce for groundwater applications, which can potentially be alleviated by hybrid modelling schemes. Hybrid models integrate domain knowledge or physically based simulations into data-driven models.

The overarching question is how to extract as much information as possible from available data sources, i.e. observations, domain knowledge or physical-based simulations and how to consolidate them most efficiently in data-driven modelling frameworks. Data-driven models include, but are not limited to time series models, machine learning / deep learning models, statistical models or lumped groundwater models. These models can be used for diverse purposes, including the prediction of historic, current and future groundwater levels or groundwater quality parameters, assessing the impact of anthropogenic activities, or enhancing conventional physically based groundwater modelling approaches.

This session welcomes contributions on the development of:
• New and improved data-driven methods for prediction or exploration of groundwater quantify or quality in space and/or time.
• Concepts and approaches for regionalization and transferability, such as the spatial transfer to ungauged sites or the temporal extrapolation to unseen conditions.
• Application of machine learning techniques for uncertainty quantification and sensitivity analysis.
• Approaches to improve hydrogeological system understanding from data-driven models and their parameters through e.g., response functions, explainable and interpretable machine learning.
• Real-world applications and comparative studies that employ data-driven methods to address groundwater challenges.
• Approaches to address common challenges in monitoring data, such as non-stationarity of time series, irregular time steps and data scarcity.
• Methods for the analysis of big data and complex datasets from the groundwater domain.
• Hybrid models combining machine learning techniques with conventional physically based groundwater models.
• Machine learning based emulation (surrogate models) of physically based groundwater models for enhanced groundwater modelling and data assimilation.

In the European Union, 38 billion m3 of groundwater are extracted every year for municipal water supply, contributing 2/3 of the drinking-water supply. Industrial groundwater extractions are on the same order of magnitude, whereas the groundwater demand for irrigation agriculture is about 15 billion m3 (1, 2). The main threats for groundwater resources are overexploitation and contamination, with strong regional differences: Groundwater resources in the Mediterranean are affected the most by unsustainable extraction for agriculture, whereas regions with poor chemical status of groundwater coincide with those of intensive agriculture (modulated by soil type) or a long history of industry. Climate change and population growth increase the pressure on water resources. A comprehensive understanding of groundwater resources and competing usages is of crucial importance for its sustainable management, and thus for future water supply and ecosystem functioning.
The proposed session will cover current developments and innovations on the assessment of groundwater resources, projections of future supply and demand, and strategies for sustainable groundwater management. The session will address all aspects of groundwater quantity and quality, ideally with its coupling, relevant for long-term management. Contributions may focus on integrative assessing that includes specific threats (e.g. agricultural contamination, excessive withdrawals, pathogens, seawater intrusion), future projections, the challenges of allocating water to different purposes (municipal water supply, industry, agriculture, ecology). We also welcome contributions on assessing emerging demands (e.g., thermal use of aquifers) and on method developments (e.g., integrative modelling, new monitoring approaches, bio-indicators, isotopic tracers). Technical solutions (e.g., artificial groundwater recharge, in situ treatment ) and management strategies including stakeholder involvement, participatory approaches and the consideration of governance and economic requirements are also welcome.
Integrative contributions will be given preference.
(1) European Environment Agency (EEA), 2022, Europe’s groundwater - a key resource under pressure, doi: 10.2800/629513
(2) https://data.apps.fao.org/aquastat, data for 2021

This session deals with the use of geophysical methods for the characterization of subsurface properties, states, and processes in contexts such as hydrology, ecohydrology, contaminant transport, reactive media, etc. Geophysical methods potentially provide subsurface data with an unprecedented high spatial and temporal resolution in a non-invasive manner. However, the interpretation of these measurements is far from straightforward in many contexts and various challenges remain. Among these are the need for improved quantitative use of geophysical measurements in model conceptualization and parameterization, and the need to move quantitative hydrogeophysical investigations beyond the laboratory and field scale towards the catchment scale. Therefore, we welcome submissions addressing advances in the acquisition, processing, analysis and interpretation of data obtained from geophysical and other minimally invasive methods applied to a (contaminant) hydrological context. In particular, we encourage contributions on innovations in experimental and numerical methods in support of model-data fusion, including new concepts for coupled and joint inversion, and improving our petrophysical understanding on the link between hydrological and geophysical properties.

The rising demand for agricultural production combined with the growing pressures of climate change has driven a substantial increase in the use of pesticides and fertilizers to boost crop yields. While these inputs are critical for meeting global food needs, they pose serious risks to groundwater and subsurface water resources, with significant implications for human health and ecosystems.
Through this session, we aim to advance interdisciplinary collaboration among researchers, policymakers and stakeholders to investigate the complex dynamics between pesticide and fertilizer application, evolving agricultural practices, climate change, and the subsequent effects on groundwater and subsurface water quality.
Topics of Interest
1- Pesticide and fertilizer fate and transport in groundwater and subsurface water
2- Impact of agricultural practices on groundwater and subsurface water quality
3- Interactions between climate change and agricultural inputs on groundwater contamination
4- Sustainable agricultural practices for minimizing pesticide and fertilizer use and protecting groundwater resources
5- Policy and management strategies for addressing groundwater contamination issues
6- Case studies of successful groundwater protection and restoration efforts

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

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

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

Fractured-porous and karst media constitute one of the most challenging geological systems to study due to their complex geometry patterns and hence associated scale-specific hydraulic and transport relevant properties. Because of their widespread distribution, such systems are of central importance for various research communities including hydrogeology and groundwater resources, geothermal systems, CO2 sequestration, nuclear waste repository site vulnerability, earthquake and volcano hazard assessment, and petroleum and mining engineering. They are subject to an extensive spectrum of methods for characterization and modeling of flow and transport dynamics, encompassing laboratory experiments, field studies, numerical simulations, and analytical techniques. The multiscale nature of fractured-porous and karst media poses significant challenges for coupling micro and macro scales, which is crucial for accurate representation and prediction of speleogenesis, reactive transport and the response to natural and anthropogenic boundary conditions. Addressing these challenges requires integrating approaches across different scales and leveraging advances in computational and analytical methods and deployment of state-of-the-art laboratory and field devices. We welcome contributions ranging from pore to field scales that focus on structural-geological characterization, characterization of flow and transport processes in the vadose and phreatic zone, as well as multiscale-coupling approaches. Topics of interest include, but are not limited to: (1) Advances in laboratory techniques, in-situ field methods, and analytical techniques for examining and understanding pore-scale to field-scale properties and behaviors; (2) Development and application of models to quantify and simulate complex flow and transport processes across multiple scales, enhancing predictive capabilities and practical; (3) Studies addressing water resource management, contamination remediation, environmental impact assessments, and the role of subsurface fracturing in earthquake and volcano hazard assessments; (4) Research aimed at improving the efficiency and safety of resource extraction in petroleum and mining engineering, as well as optimizing the exploitation of geothermal resources.

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.

This session aims to bring together scientists working in the field of vadose zone hydrology across spatial scales ranging from the pore- to the catchment- and continental scale. Recent regional and continental-scale drought events and flood events urge the need for better understanding the role of vadose zone processes in the Earth system. The state of the vadose zone controls biogeochemical processes, nutrient and pollutant transport, catchment response functions, land-atmosphere exchange, and rainfall-runoff processes. In addition, the vadose zone as part of the critical zone provides important ecosystem services. Key research challenges include amongst others improving characterization of vadose zone properties, reducing uncertainty in quantifying vadose zone water fluxes including exchange with aquifers and surface waters and feedbacks within the soil-vegetation-atmosphere continuum. Guided by advanced sensor technologies, high-frequency observations and reanalysis, scientists are able to bridge scales and deduct processes at unprecedented resolutions for an in-depth more data-driven understanding of vadose zone processes.

In tandem with big data availability, new methods in machine learning and artificial intelligence may provide additional methodological capacity to understand the role of vadose zone, especially when tackling dynamic behavior of vadose zone properties as a result of changing frequency, duration and magnitude of drought and flood events.

We invite you to submit contributions from experimental, field and laboratory studies as well as synthetic and modeling studies from the pore to continental scales. Contributions to this session include soil hydrological processes, characterization of soil properties, soil biogeochemical processes, transport of pollutants, and studies on the soil-vegetation-atmosphere system. Presentations of novel, interdisciplinary approaches and techniques are also highly welcome.

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

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 proper management of blue and green water is vital for sustainable livelihoods and agricultural practices around the world. This is especially true in drylands, where any productive activity is deeply related to the understanding of soil hydrological behaviour, and irrigation is both a pillar of agroecosystems and a defence against desertification, but also in temperate or humid lands which can experience variations in the hydrological cycle and be prone to water scarcity due to climate change.
Improper practices, which are not able to cope with climate-induced variability and anomalies, may in fact contribute to soil degradation and depletion of the available water sources. For example, incorrect irrigation techniques may lead to soil and groundwater salinization, with dramatic fallout on agricultural productivity, while overgrazing may lead to exploitation of vegetation cover, soil compaction, and adverse effects on the soil capability of water buffering. 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 drylands and environments under actual or projected stress conditions (e.g. water shortage, compaction, salinization)
- The interaction between irrigation and soil hydrology including deep drainage
- 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 the use of non-conventional waters (e.g. water harvesting), and managed aquifer recharge systems
- The management of rangeland areas, including their restoration

This session is co—sponsored by the International Commission on Irrigation and Drainage (ICID, to be confirmed) and the International Center for Agriculture Research in the Dry Areas (ICARDA, to be confirmed).

The interactions between plants and the environment play a prominent role in terrestrial fluxes and biochemical cycles. However, we still lack detailed knowledge of how these interactions impact plant growth and plant access to soil resources, particularly under deficient conditions. The main challenge arises from the complexity inherent to both soil and plants. To address these knowledge gaps, an improved understanding of plant-related transfer processes is needed.

Experimental techniques such as non-invasive imaging and three-dimensional root system modeling tools have deepened our insights into the functioning of water and solute transport processes in the soil-plant system. 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 plant-related resource transfer processes across different scales (from the rhizosphere to the global scale) and welcomes scientists from multiple disciplines encompassing the soil and plant sciences. We are specifically inviting contributions on the following topics:

- Identification of plant strategies to better access and use resources from the soil, including under abiotic stress(es)
- Bridging the gap between biologically and physically oriented research in soil and plant sciences
- Measuring and modeling of soil-plant hydraulics, water and solute fluxes through the soil-plant-atmosphere continuum across scales.
- Novel experimental and modeling techniques assessing below-ground plant status and processes such as root biomass, root growth, root water and nutrient uptake, root exudation, microbial interactions, and soil aggregation
- Mechanistic understanding of drought impact on transpiration and photosynthesis and their predictions by earth system models

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

The concept of ‘Man as a geological agent’ in the Anthropocene, leading to profound changes (e.g. biodiversity, climate, land and water degradation) in the Earth's surface processes, is now widely accepted beyond the Earth Science community.
Environmental pollution and degradation are expected to intensify in the coming decades as pressure on terrestrial ecosystems and hydrosystems increases in the context of climate change.
The retro-observation of environmental responses to human disturbance can help to promote more responsible and sustainable land and water resources management policies in the future. The collection and multidisciplinary analysis of recently deposited sediments in lakes, dam reservoirs, and fluvial systems provide a unique and powerful tool for learning from the past to retrospectively reconstruct the inertia, trajectories, and resilience of terrestrial and aquatic ecosystems to anthropogenic forcing.

In this session, we invite studies that examine sediment dynamics perturbed by human activities over the past few centuries to recent decades. We encourage contributions showing the consequences of human-induced land use changes (e.g. deforestation, agricultural expansion), pollutant releases (e.g. metals, organic substances, microplastics), changes in biodiversity, etc., in particular those developing innovative methods and proxies applied to recent sediment records to understand better the impacts of these activities on land/water resources at different spatial and temporal scales.

Hydromorphological processes, including sediment erosion, transport, and deposition, are crucial in shaping open water environments such as rivers, estuaries, lakes, and reservoirs. Accurate predictions of these processes are essential for both research and practical applications. Over the past decades, numerical models have become vital tools in hydraulic engineering and geosciences for simulating these complex interactions. With advances in algorithms and computational power, high-resolution simulations of water, sediment, and air interactions are now possible. Additionally, the growing availability of high-quality validation data from lab experiments and field studies has enhanced these models, leading to new insights into processes like dune development, riverbed armoring, and density-driven transport. As a result, next-generation numerical modeling techniques are enabling the exploration of intriguing questions in hydromorphology. Furthermore, Artificial Intelligence (AI) is emerging as a reliable alternative in these studies.

This session aims to unite scientists and engineers who develop, improve, or apply numerical models of multiphase flows for sediment transport in open water environments. We welcome contributions that cover a range of spatiotemporal scales, from small-scale particle entrainment to large-scale morphological development, in various settings including rivers, lakes, reservoirs, estuaries, and coastal areas.

Contributions may include, but are not limited to:
- Sediment entrainment processes, ranging from cohesive sediments to armored riverbeds
- Bed load and suspended sediment transport, including flocculation
- Simulation of sediment management for the planning, operation, and maintenance of hydropower plants
- Design and assessment of river restoration measures
- Navigation-related issues, such as sediment replenishment, dredging, and erosion caused by ship-generated waves
- Flood-related impacts, including the long-term effects of morphological bed changes on flood security
- Eco-hydraulics, focusing on flow, sediment, and vegetation interactions
- Density-driven transport mechanisms.

Please note that the session “Hydro-morphological Processes in Open Water Environments – Measurement and Monitoring Techniques” shares a similar focus. If your contribution is more centered on measurement and monitoring, we encourage you to submit your abstract to that session instead.

The main goal of this session is to bring together the community of scientists, scholars, and engineers, investigating, teaching, and applying novel measurement techniques and monitoring concepts, which are crucial to analyze sedimentary and hydro-morphological processes in rivers, lakes and reservoirs, estuaries as well as in coastal and maritime environments. This session focuses on the evaluation and quantification of bed load and suspended load, bedforms migration, channel horizontal migration, bed armoring and colmation, but also on describing the mode of transport, flocculation, settling, and re-suspension of the sediment particles. In general, this session aims to attract research communities that are developing measurement techniques that contribute to the understanding of hydro-morphological changes in rivers and of the interaction between the fluvial sediment and the natural and built environment.
Contributions are welcome with a particular focus on single and combined measurement techniques, on post-processing methods as well as on innovative and advanced monitoring concepts for field and laboratory applications. Furthermore, we welcome contributions containing recent results in a temporal and spatial scale on sediment budgets as well as on sedimentary and morphodynamic processes in open water environments.

Contributions may refer, but are not restricted, to:
- Measurements of suspended sediment transport in open water environments, e.g., with optical, acoustical, traditional sampling methods or others;
- Measurements of bed load transport, e.g., with bed load samplers, sediment traps, tracers or acoustic and optical methods;
- Determination of sediment characteristics, e.g., with mechanical bed material samplers or freeze core technique.
- Innovative measurement approach or techniques aimed for validation and calibration of numerical models;
- Measurements of critical bed shear stress of cohesive sediments, e.g., with benthic flumes or miscellaneous devices;
- Monitoring of morphological changes like lake and reservoir sedimentation, bank erosion or bed armoring, meandering migration, river bends evolution;
- Measuring networks / multiple point datasets;
- Large or small scale monitoring concepts including case studies;
- In-situ or laboratory calibration of measurement data using classical or novel (e.g., machine learning) approaches.

Obtaining quantitative information on the spatial pattern of soil redistribution during storms and on the spatial sources supplying sediment to rivers is required to improve our understanding of the processes controlling these transfers and to design effective control measures. It is also crucial to quantify the residence times of material transiting rivers along the sediment cascade, and to reconstruct the potential changes in sources that may have occurred in the past at various temporal scales. This need has been reinforced by the acceleration of impacts associated with climate and land use change driving increased erosion and excess sediment pollution of freshwater and marine environments.
During the last few decades, several sediment tracing or fingerprinting techniques have contributed to provide this information, in association with other methods (including soil erosion modelling and sediment budgeting). However, their widespread application is limited by several challenges that the community should address as priorities.
We invite contributions that address any of the following aspects:
• Developments of innovative field measurement and sediment sampling techniques;
• Soil and sediment tracing techniques for quantifying soil erosion and redistribution;
• Sediment source tracing or fingerprinting studies, using conventional (e.g. elemental/isotopic geochemistry, fallout radionuclides, organic matter) or alternative (e.g. colour, infrared, particle morphometry) approaches;
• Investigations of the current limitations associated with sediment tracing studies (e.g. tracer conservativeness, tracer selection, 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);
• The association of conventional techniques with remote sensing and emerging technologies (e.g. LiDAR);
• Integrated approaches to developing catchment sediment budgets: linking different measurement techniques and/or models to understand sediment delivery processes.

To control catchment hydrology and morphology, and regulate water resources and forest and agricultural activities, channel control structures (such as check dams) and soil conservation techniques (e.g., terracing, mulching, afforestation) have been strategically used for several decades. Although research has underscored their vital role, several scientific aspects remain unexplored: i) suitable planning and design of restoration actions; ii) prediction of degradation and functioning over time; iii) quantification of the effectiveness of actions as a function of their desired purposes; iv) assessment of their effectiveness after extreme hydrological events. The lack of long-term monitoring studies makes this scientific objective complicated. However, remote sensing (RS) opens new horizons to monitor the evolution of catchment morphology and analyse past and current phenomena by exploiting multi-temporal surveys at different scales and open-source big data.
This session offers a platform for collaboration and discussion among soil scientists, hydrologists, geomorphologists, foresters and stakeholders, facilitating a dialogue on critical issues about planning, design, and management of torrent control works and soil conservation techniques at the catchment scale. Research about the following topics is welcome: i) innovative protocols and guidelines for planning and design; ii) emerging techniques for multi-temporal or real-time monitoring of effects exploiting RS; iii) standards for comprehensive analysis of structural and functioning conditions as well as impacts on natural dynamics of torrents and their catchments; iv) identification of new challenges (i.e., soil-bioengineering techniques and integration of living vegetation in check dam systems).
Early career scientists are encouraged to contribute to the session with original and advanced studies.

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 thus focuses on sources, transport pathways, storage and re-mobilization, and travel times of sediments and contaminants across temporal and spatial scales, as well as their impact on catchment and freshwater ecosystems.

This session particularly addresses the following issues:
- Delivery rates of sediments and contaminants from various sources (i.e. agriculture, urban areas, mining, industry or natural areas);
- Transport, retention and remobilization of sediments and contaminants in catchments and river reaches;
- Modelling of sediment and contaminant transport on various temporal and spatial scales;
- Biogeochemical controls on contaminant transport and transformation;
- Studies on sedimentary processes and morphodynamics, particularly sediment budgets;
- Linkages between catchment systems and lakes, including reservoirs;
- Analysis of sediment archives to appraise landscape scale variations in sediment and contaminant yield over medium to long time-scales;
- Impacts of sediments and contaminants on floodplain, riparian, hyporheic and other in-stream ecosystems;
- Response of sediment and contaminant dynamics in catchments, lakes and rivers to changing boundary conditions and human actions;
- Assessing human impact on landforms and geomorphological processes in sediment and contaminant transport.

Ecohydrology, i.e., the study of the interactions between water and ecosystems, is expanding 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.

Forest ecosystems interact very strongly with hydrological processes, at various spatial and temporal scales. They have co-evoloved with soils and topography over a long period of time, and their potentially deep root systems enable cross-cutting exchange between the ground water, soil water, plants and the atmosphere. Our ability to detect these sometimes hidden interactions is limited, but new techniques, such as geochemical and isotopic tracers, various geophysical and remote sensing techniques provide ever new and often surprising perspectives into the complex interactions between forest ecoystems and the water cycle.
This session solicits contributions that share new insights about forest ecohydrological processes or demonstrate new ways of observing and modelling water fluxes in forest ecoystems, forest water stress, drought resistance and resilience, and the links between forest hydrological processes and the wider water, carbon and nutrient cycles.

Peatlands develop in specific hydrological settings and are highly sensitive to changes in hydrological conditions and climate. For example, both peat hydrological properties and peatland greenhouse gas balance can change drastically after disturbances such as drainage, permafrost thaw, or mechanical compaction. Hydrological conditions are also a key control for a number of the ecosystem services offered or regulated by peatlands, including biodiversity, carbon storage, and nutrient retention. In addition, the role of pristine and disturbed peatlands in flood retention, support of low flows and regional climate remains debated. As hydrological and biotic processes in peatlands are strongly coupled, predicting the eco-hydrological effects of climate change, degradation, and restoration on peatland ecosystem responses—including greenhouse gas emissions—is a demanding task for the peatland community.

This session addresses peatland hydrology and its interaction with ecosystem processes in all latitudes. We especially encourage papers on permafrost and tropical peatlands for which field studies are scarce and inclusion into Earth system models is largely pending. We invite submissions on: (1) hydrological processes operating in all types of peatlands (pristine, disturbed, degraded, drained, managed, rehabilitated or re-wetted) in boreal, temperate, and tropical latitudes; and (2) the first-order control of peatland hydrology on all kinds of peatland functions.

We aim to advance the transfer of knowledge and methods and welcome laboratory, field, remote sensing, and modeling studies on hydrological, hydrochemical, biogeochemical, ecohydrological or geophysical topics, as well as ecosystem service assessments.

Held annually 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.

This session addresses the complex challenge of understanding, representing, predicting and managing lentic inland waters, such as lakes and reservoirs, and their ecosystems in the context of their catchments. The focus is twofold:
- understanding and linking physical, chemical and ecological processes in lakes and reservoirs with both natural and anthropogenic influences from their catchments. Key factors include nutrient loading, floods and droughts, land use changes, forest fires, sediment inputs, and road salting.
- exploring the role of lakes and reservoirs management, including hydropower generation, water level regulation and flushing techniques, and their impact on rivers, groundwater and the overall aquatic environment both upstream and downstream.
In this way, the session aims to bridge limnology and hydrology into a common understanding of how to better connect lakes and reservoirs to their catchments to ultimately advance our understanding of inland waters and improve water management practices.
We welcome contributions based on experimental research, monitoring, modelling, machine learning, and remote sensing, with a focus on developing integrated lake-catchment approaches.

Groundwater-surface water interfaces are crucial for the continuity of aquifer-river and aquifer-lake systems. These interfaces include various interconnected zones such as hyporheic zones, benthic zones, riparian corridors, and lake sediments, where bidirectional interactions between surface water and aquifer occur. Current research focuses on the effects of water exchange on the transport and transformation of nutrients, microplastics, and pollutants. It also addresses the control of heat, oxygen, and organic matter budgets available to microorganisms and macroinvertebrates in sediments. However, 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 at different spatial and temporal scales, such as river channels, alluvial aquifers, and regional groundwater flow. 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 interface 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.

With the recent declaration of the Hydrology Renaissance era, the perspectives on river networks and watersheds in hydrological sciences have remarkably broadened, moving from channels merely draining water fluxes to complex ecological corridors transporting energy and materials and connecting terrestrial and aquatic ecosystems. This new viewpoint requires a comprehensive understanding of the coupled hydrological, biogeochemical and ecological processes occurring in river networks and across watersheds. Hydrological drivers shape the spatial structure and connectivity of riverine ecosystems (e.g., transport of nutrient and organic resources, organism dispersal), while ecological communities affect regional hydrology (e.g., through transpiration, ecosystem engineering) and release in the water biological substances (e.g., organic matter, environmental DNA) which provide information on hydrological pathways.
This session aims at fostering the exchange of novel interdisciplinary research findings on the interplay of hydrological, biogeochemical and ecological processes in riverine systems and watersheds. We welcome studies on ecohydrological dynamics, riverine metacommunities and food webs, stream metabolism, eutrophication, carbon and/or nutrient cycling, as well as research considering the impacts of anthropogenic interventions on interactions between these processes. We are particularly interested in contributions where tools and methods from one discipline are used to gain insights in another. Contributions employing a range of theoretical methods, monitoring techniques (e.g., in-situ, remote sensing) and/or modelling approaches (e.g., statistical, process-based, machine/deep-learning-based) at diverse spatial scales – from individual watersheds or streams to entire river networks – are highly encouraged.

For most of the last century, traditional limnological research has heavily relied on fieldwork, with a relatively small fraction of lakes subjected to extensive, in-depth investigations. High temporal resolution and long-term in-situ observations, often combined with well-calibrated and validated models, have so far provided detailed knowledge of the physics and ecology governing the overall behavior of a few lakes worldwide.
The latest advancements in limnological research have demonstrated the potential for upscaling from single-lake studies to global-scale applications. Such advancements have been made possible through the synoptic-scale coverage and availability of remote sensing products integrated with numerical modeling, as well as the development of global-scale datasets of in-situ observations. While remote sensing data primarily informs on surface features, coupling with models has enabled its extensive use in inspecting internal dynamics and shifts in mixing regimes.
In the current context of limnological research, a global approach is emerging as a means to assess the impacts of anthropogenic activities on both the quantity and quality of lake waters. However, upscaling inevitably introduces uncertainties and inaccuracies, raising concerns about the reliability of global conclusions at the single-lake scale.
This session welcomes contributions that apply an upscaled approach to limnological research. We invite studies that employ global datasets of satellite-derived or in-situ lake variables, physically based models, as well as hybrid models or AI-based algorithms, to draw conclusions on the past and/or future behavior of lakes at regional to global scales, analyzing long-term changes or studying the effects of extreme events. Emphasis will be placed on contributions that stimulate discussion about the limits, current challenges, and overall opportunities and potentialities of limnological investigations at global scales.

At the catchment scale, ecohydrology – an interdisciplinary field merging principles from ecology, hydrology, biology, and geomorphology – is crucial for understanding the interactions among energy, water, and carbon cycles that sustain and define the functioning of catchments. Key ecohydrological fluxes include plant (evapo)transpiration, primary productivity, and autotrophic and heterotrophic respiration. The “green” and “blue” components of a catchment, representing its terrestrial and riverine environments, respectively, play significant roles in shaping these fluxes. In terrestrial environments, above-ground vegetation and below-ground biomass are the primary contributors. In riverine environments, flowing water (blue water) is not only essential for nutrient transport but also for nutrient processing.
This session aims to highlight interdisciplinary ecohydrological research, focusing on (but not limited to): theoretical, numerical modeling and remote sensing that improve our understanding of water and carbon fluxes in catchments and their interactions. Contributions may span different climatic contexts, from small to large catchments, to highlight the relevance of both green and blue water in changing environments.

Stable isotopes are powerful tools for tracing water fluxes and associated nutrients in the soil-plant-atmosphere continuum. Given the complex interactions between subsurface water fluxes, plant water uptake and atmospheric drivers, new field- and laboratory-based methods should enable observations of ecohydrological processes at a high temporal and spatial resolution and with high precision and accuracy. At the same time, ecohydrological models shed new light on water and nutrient fluxes in the soil-plant-atmosphere continuum. We welcome experimental and modelling studies that present methodological developments and applications of isotope tracers to improve our process knowledge of water and nutrient fluxes between the subsurface, plants and the atmosphere, across different scales (from plant and forest stand up to the catchment scale). In our session, we aim to discuss i) innovative process-based interpretations from stable isotope data, ii) novel methods of model applications and data analysis, as well as iii) current methodological developments. We aim to foster interdisciplinary exchange between the various fields assessing ecohydrological processes using natural tracers, including research in groundwater and vadose zone hydrology, plant physiology, and ecology.

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) evaluate challenges and opportunities of using AI for in-situ scaling and comparisons.

This session is dedicated to discovering environmental DNA (eDNA), organic matter (OM), and community structures of, for example, diatoms or other microbes as innovative tools to trace water and sediment transport within and across landscapes and ecosystems. These new techniques bring cutting-edge approaches in biology to hydrological process research. We explore the methodologies, applications, and implications of their integration.

Presentations within this session will center on understanding and characterizing the movement of biological tracers within hydrological systems, considering factors such as their distribution, degradation characteristics, transport mechanisms, and interactions with environmental parameters. Moreover, this session will showcase advancements in laboratory techniques and modeling approaches tailored to simulate the transport dynamics of biological tracers in hydrological systems. Presentations will highlight accuracy, resolution, and complexity improvements, fostering discussions to enhance our predictive capabilities and understanding of tracer behavior. Influential variables such as water flow, sediment dynamics, temperature, and nutrient availability will be explored. Key processes to be addressed include tracer deposition, uptake, and transformation, shedding light on their role in shaping hydrological processes and ecosystem functioning.

While we’ll primarily focus on DNA analysis, carbon tracing techniques, and diatom characterization, we also welcome contributions employing additional approaches such as modeling and theoretical concepts. We look forward to your contributions that explore the intersection of biology and hydrology, which we hope will pave the way for interdisciplinary collaborations and breakthroughs in environmental science.

Discover the basics of Geodesy and geodetic data! Geodetic data, from GNSS to gravity measurements, play a crucial role in various Earth sciences, including hydrology, glaciology, geodynamics, oceanography, and seismology. Curious about what these data can (and cannot) tell us? This short course offers a crash course in core geodetic concepts, giving you the insights you need to better understand the advantages and limitations of geodetic data. While you won’t become a full-fledged geodesist by the end, you’ll walk away with a clearer picture of how to use these datasets across various fields. Led by scientists from the Geodesy division, this course is open to all, whether you frequently work with geodetic data or are simply curious about what geodesists do. Expect lively discussions and practical insights. For all geodesists, get the chance to learn what non-geodesists need when working with geodetic data!

This 60-minute short course is part of a quintet of introductory 101 courses on Geodesy, Geodynamics, Geology, Seismology, and Tectonic Modelling. All courses are led by experts who aim to make complex Earth science concepts accessible to non-experts.

Effective risk communication is crucial for enhancing public understanding and response to disaster risks. This short course is designed to equip students, early-career scientists, experienced researchers, and science communicators with advanced tools and strategies for effective risk communication. Participants will learn about fundamental principles of risk communication, cognitive biases, risk perception, and the use of media and social media in conveying risk information. The course will also address how to adapt communication strategies to different environments and audiences, beyond the traditional sharing of scientific data. Contributing to the European Commission’s disaster resilience goal no. 2 on ‘Prepare - Increasing risk awareness and preparedness of the population’ and the preparEU programme, the course will provide practical skills to improve risk communication efforts and foster more resilient communities. Attendees are welcome to join the scientific session and splinter meetings, creating a unified path for those interested in a comprehensive exploration of risk communication

Data assimilation (DA) is widely used in the study of the atmosphere, the ocean, the land surface, hydrological processes, etc. The powerful technique combines prior information from numerical model simulations with observations to provide a better estimate of the state of the system than either the data or the model alone. This short course will introduce participants to the basics of data assimilation, including the theory and its applications to various disciplines of geoscience. An interactive hands-on example of building a data assimilation system based on a simple numerical model will be given. This will prepare participants to build a data assimilation system for their own numerical models at a later stage after the course.
In summary, the short course introduces the following topics:

(1) DA theory, including basic concepts and selected methodologies.
(2) Examples of DA applications in various geoscience fields.
(3) Hands-on exercise in applying data assimilation to an example numerical model using open-source software.

This short course is aimed at people who are interested in data assimilation but do not necessarily have experience in data assimilation, in particular early career scientists (BSc, MSc, PhD students and postdocs) and people who are new to data assimilation.

Visualisation of scientific data is an integral part of scientific understanding and communication. Scientists have to make decisions about the most effective way to communicate their results every day. How do we best visualise the data to understand it ourselves? How do we best visualise our results to communicate with others? Common pitfalls can be overcrowding, overcomplicated or suboptimal plot types, or inaccessible colour schemes. Scientists may also get overwhelmed by the graphics requirements of different publishers, for presentations, posters, etc. This short course is designed to help scientists improve their data visualisation skills so that the research outputs would be more accessible within their own scientific community and reach a wider audience.
Topics discussed include:
- golden rules of DataViz;
- choosing the most appropriate plot type and designing a good DataViz;
- graphical elements, fonts and layout;
- colour schemes, accessibility and inclusiveness;
- creativity vs simplicity – finding the right balance;
- figures for scientific journals (graphical requirements, rights and permissions);
- tools for effective data visualisation.
This course is co-organized by the Young Hydrologic Society (YHS), enabling networking and skill enhancement of early career researchers worldwide. Our goal is to help you make your figures more accessible to a wider audience, informative and beautiful. If you feel your graphs could be improved, we welcome you to join this short course.

Extreme event attribution (EEA) emerged in the early 2000s to assess the impact of human-induced climate change on extreme weather events. Since then, EEA has expanded into different approaches that help us understand how climate change influences these events.

In unconditional approaches, such as the risk-based method, the oceanic and atmospheric conditions are largely left unconstrained. In contrast, conditional approaches focus on constraining the specific dynamics that lead to an event. One example is the analogues approach, where the synoptic atmospheric circulation is held relatively fixed. Both approaches can be used to assess changes in the likelihood, intensity, or both, of extreme events.

In this short course, we will examine the robustness of the analogues method for EEA, explore different strategies for defining analogues, and discuss their applications in attribution studies.

In a changing climate world, extreme weather and climate events have become more frequent and severe, and are expected to continue increasing in this century and beyond. Unprecedented extremes in temperature, heavy precipitation, droughts, storms, river floodings and related hot and dry compound events have increased over the last decades, impacting negatively broad socio-economic spheres (such as agriculture), producing several damages to infrastructure, but also putting in risk human well-being, to name but a few. The above have raised many concerns in our society and within the scientific community about our current climate but our projected future. Thus, a better understanding of the climate and the possible changes we will face, is strongly needed. . In order to give answers to those questions, and address a wide range of uncertainties, very large data volumes are needed across different spatial (from local-regional to global) and temporal scales (past, current, future), but sources are multiple (observations, satellite, models, reanalysis, etc), and their resolution may vary each other. To deal with huge amounts of information, and take advantage of their different resolution and properties, high-computational techniques within Artificial Intelligence models are explored in climate and weather research. In this short-course, a novel method using Deep Learning models to detect and characterize extreme weather and climate events will be presented. This method can be applied to several types of extreme events, but a first implementation on which we will focus in the short-course, is its ability to detect past heatwaves. Discussions will take place on the method, and also its applicability to different types of extreme events. The course will be developed in python, but we encourage the climate and weather community to join the short-course and the discussion!

Database documentation and sharing is a crucial part of the scientific process, and more scientists are choosing to share their data on centralised data repositories. These repositories have the advantage of guaranteeing immutability (i.e., the data cannot change), which is not so amenable to developing living databases (e.g., in continuous citizen science initiatives). At the same time, citizen science initiatives are becoming more and more popular in various fields of science, from natural hazards to hydrology, ecology and agronomy.

In this context, distributed databases offer an innovative approach to both data sharing and evolution. These systems have the distinct advantage of becoming more resilient and available as more users access the same data, and as distributed systems, contrarily to decentralised ones, do not use blockchain technology, they are orders of magnitude more efficient in data storage as well as completely free to use. Distributed databases can also mirror exising data, so that scientists can keep working in their preferred Excel, OpenOffice, or other software while automatically syncing database changes to the distributed web in real time.

This workshop will present the general concepts behind distributed, peer-to-peer systems. Attendees will then be guided through an interactive activity on Constellation, a scientific software for distributed databases, learning how to both create their own databases as well as access and use others' data from the network. Potential applications include citizen science projects for hydrological data collection, invasive species monitoring, or community participation in managing natural hazards such as floods.

Data imperfection is a common feature in Geosciences. Scientists and managers alike are faced with uncertain, imprecise, heterogeneous, erroneous, missing or redundant multi-source data. Traditionally, statistical methods were used to address these shortcomings. With the advent of Big Data, Machine Learning methods, the development of new techniques in data mining, knowledge representation and extraction as well as artificial intelligence, new avenues are being offered to tackle the shortcomings of data imperfection.
This session aims to provide a venue to exchange on the latest progress in assessing, quantifying and representing data imperfection in all of its forms. We welcome abstracts focused on, but not limited to:
- Use cases and applications from all fields of Geosciences on missing value imputation, data fusion, imprecision management, model inversion. Examples may be built on any type of data: alpha-numerical time series, georeferenced field data, satellite, areal or ground imagery, geographical vector data, videos, etc...
- Theoretical developments for data fusion and completion; uncertainty assessment and quantification, knowledge extraction and representation from heterogeneous data, reasoning and decision making under uncertainty.
- Multi-disciplinary approaches including artificial intelligence and geosciences are encouraged. Contributions addressing data issues and solutions related to participatory sciences, crowd-sourced data and opportunistic measurements will be particularly appreciated.

In the Anthropocene, water resources are simultaneously under unprecedented stress and the foundation for most ecosystem and societal processes. It is more important than ever to thoroughly understand the hydrological cycle and its interactions with other complex physical systems and social dimensions to address water-related challenges and develop actionable, sustainable solutions. To do this effectively, we need to move beyond a “science-as-usual” approach and leverage transdisciplinary knowledge involving multiple actors, including scientists, policymakers, local communities and indigenous peoples, NGOs and local associations, media, and businesses. Each of these actors brings a unique perspective and expertise, and we must empower and value their contributions with practices such as co-creation, to arrive at integrated solutions for complex water management issues. Co-creation can be defined as an iterative and collaborative process of mutual learning in which different knowledge interact and are integrated to address complex societal issues. Such approaches are common in policy creation and public services development but up until now have been under-described, -formalized, and -utilized in the context of water resources management and hydrological sciences.
Therefore, 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; meta-analyses, review of other experiences, and literature reviews; critical geography, political ecology and other critical approaches to co-creation and stakeholders involvement in water resources decision making.

Co-organized by the Working Group on Co-Creation of Water Knowledge of the International Association of Hydrological Sciences: https://iahs.info/uploads/HELPING/WG%20Proposal%20Co-Creating%20Water%20Knowledge%20v2.pdf

The continuous increase of world’s cities sprawl, in a context of global change, makes it urgent to promote the sustainability of these areas. But an integrated and systemic approach is required to face with simultaneous environmental, economic and social challenges. The concept of critical zone offers an adapted framework to develop integrated approach, but it needs to be adapted to the specificities of the zones where humans live and work. The critical zone is defined initially as the thin and heterogeneous and near surface environment in which occur interactions involving rock, soil, water, air, and terrestrial ecosystems. In urban areas, the critical zone is strongly transformed by the infrastructure, facilities and buildings, and impacted by human activities and usages which heavily affect the fluxes and balances of water, energy, and chemicals including pollutants….In this session, we will address the question of the biophysical processes specificities of the urban critical zone that interact with anthropic processes controlled by human activities and stakeholders. Most of the urban geophysical processes are studied are very local and small levels, it is necessary to produce interdisciplinary knowledge are more global scales.

We invite contributions of experience on urban critical zones and especially those including observations, measurements of fluxes, description of biogeochemical, physical and human resilience processes and development of models to respond to these crosscutting issues. Proposals coming from diverse urban contexts (size, growth patterns, geographical, social) at different spatial and temporal scales will be appreciated. We aim at forstering interdisciplinary dialogue to make the Urban Critical Zone a unifying concept.

Plastic pollution is ubiquitous in terrestrial, freshwater, and marine ecosystems. Reliable data on plastic abundance and fluxes are crucial to study its sources, sinks, transport dynamics, and impact. Furthermore, long-term and large-scale monitoring is required to design, implement, and assess plastic pollution prevention and reduction measures. In this session we invite contributions that present recent advances in plastic pollution monitoring across the entire Geosphere (atmosphere, land surface, soil, rivers, estuaries, oceans and beyond). Presentations may focus on:
• Novel monitoring methods, including advanced techniques (e.g. remote sensing, multi/hyperspectral cameras, acoustic sensors, artificial intelligence);
• Monitoring strategies, including large-scale and long-term efforts, and citizen science approaches;
• All plastic size ranges, from nano to macro;
• Baseline studies to assess current plastic pollution levels;
• Long-term trends or recent discoveries based on plastic monitoring data.
With this session we aim to bring together scientists that work on novel approaches to provide reliable data on environmental plastic pollution.

With the rapid development of modern society and economy, extensive expansion of human activities has resulted in the huge demands for wide range of synthetic organic chemicals and increases their discharge into the environment. These organic chemicals include ingredients of PPCPs, pesticides, hormones, industrial ingredients (such as flame retardants, PFASs, and plasticizers), and by-products. They are collectively termed emerging organic contaminants (EOCs).
The extensive application and presence of EOCs in our daily consumer products and the nature of these substances results in their widespread distribution with many being discharged primarily to the aquatic and soil environment. As a result, they have become ubiquitously detectable and pseudo-persistent in environments across the world with the potential for accumulation in food chains.
There has been wide ranging discussion about possible adverse effects of EOCs, such as emergence of antibacterial resistance, endocrine disrupting effects and toxicity. However, to the best of our knowledge, the risk assessment and pollution control for EOCs is challenging owing to the limited understanding of their transport, interactions and biogeochemical process among surface water, soil and groundwater interfaces/systems.
The session objective is to explore the state of the art in sampling methodologies, and lab scale, field and modelling studies for transport, interactions and biogeochemical process of EOCs between water-soil interfaces/systems, to provide a comprehensive perspective for understanding their environmental fate and behavior in the aquatic environment, for the further assessment of their potential risk and for pollution control implement. Potential topics include, but are not restricted to, the following:
• Sampling approaches for EOCs in surface water, soil and groundwater interfaces/ systems, which would include novel active sampling strategies and passive sampling techniques. Such techniques would provide important insights into process-based understanding of fate as well as for measurement campaigns on a range of spatial scales.
• Important experimental/lab scale, field and modelling studies on transport, interactions and biogeochemical process of emerging organic contaminants in sole surface water, groundwater and soil systems, and surface water-groundwater interfaces/systems, water-soil interfaces/systems surface water, and soil and groundwater interfaces/ systems.

The Sustainable Development Goals (SDGs) highlight the need for better management of water and land resources, which are increasingly subject to conflicts due to rising demographic pressures, advancing economic development, and climate change. Nature-based Solutions (NBS) are recognized as an approach that can reconcile sustainable soil and water management with the provision of various ecosystem services, such as erosion control, flood and drought mitigation, coastal protection, pollution reduction, habitat creation, recreational opportunities, and heat protection. This calls for a critical evaluation of how the NBS approach is translated into practice. Aligned with these objectives and supported by the IAHS Helping Decade, this session will explore an inter- and transdisciplinary approach to further developing NBS, including co-development with stakeholders, engaging civil society, and translating NBS into education and school curricula.
Within the scope of this session, we invite:
• Studies investigating the application of NBS in mitigating environmental extremes, such as floods or droughts;
• Studies combining NBS with social studies, including public perception surveys and the use of citizen science to assess the effectiveness of NBS;
• Studies exploring the use of NBS and related concepts in (higher) education;
• Studies combining NBS with cross-sectoral collaboration, stakeholder engagement, and transdisciplinary approaches;
• Studies investigating NBS and other sustainable management practices for soil and water conservation;
• Discussions on integrating multiple disciplines in the development of NBS, including challenges and benefits.

Human actions increasingly dominate hydrological processes worldwide, putting significant pressure on the interactions between freshwater systems, ecosystems, the Earth system and societies. The concept of system resilience is a useful but underutilised tool to address questions related to broad and varied systemic consequences of hydrological change across scales. Integrating biophysical and social-ecological system dynamics with freshwater systems under a framing of freshwater resilience advances beyond conventional approaches that characterise freshwater systems and their change in isolation. This opens pathways towards an increasingly holistic, system-of-systems conceptualization and analysis of the freshwater cycle, which is essential to understand and safeguard freshwater’s role in biosphere functioning and social well-being.

This session will incorporate studies on two overarching aspects of freshwater system resilience science. First, we are interested in how biophysical and social-ecological systems are conceptualised under the broad context of “freshwater system resilience”. We seek methodologically diverse insights on how freshwater scientists (across hydrological, environmental and social science, policy science and practitioner communities) define their systems of study and quantify the state and change of freshwater system resilience. Adding to common approaches such as hydrological modelling and Earth observation, we seek to incorporate diverse methodologies that advance, challenge, and complement these traditional methods. Studies that expand beyond scientific dimensions of freshwater resilience assessments by translating these insights into management-relevant decision support tools are equally welcomed.

The multi-scalar nature of freshwater resilience underpins both of these research themes. We invite studies that investigate freshwater resilience across local to global scales, and especially studies that consider cross-scale interactions and the scalability of functional change in integrated freshwater, social, ecological, and Earth systems.

The session aims to foster a welcoming forum to discuss the diverse and accelerating field of freshwater resilience science. We hope the session empowers the field to generate new insights on integrated hydrological, social, ecological, and Earth systems, and aids improved management of freshwater systems across scales to support social well-being and to safeguard the health of the biosphere.

Forecasting the weather, in particular severe and extreme weather, remains an important subject in meteorology. This session highlights recent research and advancements in forecasting methods, with a strong emphasis on AI-based methods and their integration into operational and impact-oriented forecasting systems. We welcome contributions that explore applications in nowcasting, mesoscale and convection permitting modelling, ensemble prediction, and seamless approaches that optimally integrate multiple forecast sources.

Topics may include:

• Data-driven forecasting, including ensemble methods, across global, regional and local scales
• Integration of data-driven models within data assimilation algorithms
• Operational workflows: implementation, monitoring, versioning of data and models, data, training, and inference pipelines
• AI-driven nowcasting methods and systems utilizing observational data and weather analysis
• Enhancement of mesoscale and convection-permitting models through AI techniques
• Application of novel remote sensing technologies in data assimilation processes
• Utilization of ensemble prediction techniques for improved forecasting
• Development of ensemble-based products for severe/extreme weather forecasting
• Seamless deterministic and probabilistic forecast prediction in data-driven, statistical, numerical and data-blending approaches
• Post-processing techniques, statistical methods in prediction
• Impact-oriented weather forecasting
• Presentation of results from relevant international research projects of EU, WMO, and EUMETNET etc.

The session invites experimentalists and modelers working on air-land interactions from local to regional scales, in vegetated and/or urban systems. The program is open to a wide range of innovative studies in micrometeorology and related atmospheric and remote sensing disciplines. The topics may include the development of new observational devices, measurement techniques, experimental designs, data analysis methods, as well as novel findings on surface layer theory and parametrization, including local and non-local processes. Theory-based contributions may encompass soil-vegetation-atmosphere transport, internal boundary-layer theories, and flux footprint analyses. Of particular interest are synergistic studies employing experimental data, parametrizations, and models addressing energy and trace gas fluxes (of inert and reactive species) as well as water, carbon dioxide and other GHG fluxes. We focus on addressing outstanding problems in land surface boundary layer descriptions such as complex terrain, effects of horizontal heterogeneity on sub-meso-scale transport processes, energy balance closure, coupling/decoupling, stable stratification and night time fluxes, dynamic interactions with atmosphere, and plants (in canopy and above canopy) and soils.

Dissolved and particulate organic carbon (DOM, POM) are key components of the global carbon cycle and are important as potential sources of CO2 and CH4, and for the long-term preservation of carbon stabilized in subsoils and sediments. DOM and POM are important sources of energy for microbial metabolism within terrestrial ecosystems, the aquatic continuum, and, ultimately, the ocean. Despite recent evidence showing this lateral transport of carbon is linked to anthropogenic perturbations, efforts to integrate DOM and POM fluxes across the terrestrial-aquatic continuum are just emerging. A comprehensive understanding of the dynamics of DOM and POM, and their interactions, in terrestrial and aquatic ecosystems remains challenging due to complex interactions of biogeochemical and hydrological processes at different scales, i.e. from the molecular to the landscape scale.
This session aims to improve our understanding of organic matter processing at the interface of terrestrial and aquatic ecosystems. We solicit contributions dealing with amounts, composition, reactivity, and fate of DOM and POM and the stoichiometry of its constituents (i.e., C, N, P, S) in soils, lakes, rivers, and the ocean as well as the impact of land use change and climatic change on these processes. For example, when assessing carbon dynamics across the terrestrial-aquatic continuum, it is important to recognize the key role of peatlands and peat restoration efforts as sources of organic matter for streams and rivers, as well as the contribution of mineral soil horizons to C fluxes at the catchment scale. Contributions addressing lateral fluxes of sediment and carbon induced by soil erosion or permafrost thaw are also welcome. We aim to bring together scientists from various backgrounds, but all devoted to the study of dissolved and/or particulate organic matter using a broad spectrum of methodological approaches (e.g. molecular, spectroscopic, isotopic, 14C, other tracers, and modeling).

Our ability to understand biogeochemical cycles of carbon, nitrogen and phosphorus and other elements in aquatic ecosystems has evolved enormously thanks to advancements in in situ sensor measurements, laboratory techniques and predictive models. The aim of this session is to demonstrate how this methodological advancement improves our understanding of coupled hydrological, biogeochemical and ecological processes in freshwater aquatic environments. In particular, our session focuses on improving the identification and quantification of the sources, delivery pathways, transformations and environmental fate of carbon and organic matter, nutrients, sediments and emerging contaminants in aquatic environments. We welcome presentations on applications of novel techniques to improve our understanding of aquatic environments and robust data-driven and modelling approaches for advanced processing of aquatic biogeochemical data. As hydrological, biogeochemical, and ecological processes undergo accelerated change, this session welcomes also studies presenting approaches and tools to monitor, model, and predict water quality and sensitivity of aquatic ecosystems to global change and human disturbance.

Nature-based climate solutions, such as conservation agriculture, forest restoration, and wetland rewetting, offer great promises to increase soil organic carbon (SOC) and reduce greenhouse gas (GHG) emissions for climate change mitigation. However, they also impact a variety of ecosystem properties such as surface albedo, energy partitioning, and hydrological cycles. To effectively measure, report, and verify (MRV) SOC changes, GHG fluxes, and climate-relevant parameters or processes, enhanced monitoring and modeling capabilities are urgently needed to comprehensively quantify the dynamics of carbon, energy, water, and nutrients in ecosystems. This session welcomes a wide range of contributions on topics related to nature-based climate solutions in agriculture, forestry, wetland, and other landscapes including, but not limited to: (1) developing scalable and cost-effective monitoring capacities through proximal and remote sensing combined with modeling to track SOC changes, GHG emissions, surface albedo, energy and water fluxes; (2) synthesizing multi-source observations to infer changes in the mentioned parameters and processes in natural and managed ecosystems; (3) developing process-based models to simulate the coupled carbon-food-water-energy processes in various landscapes; and (4) Enhancing systematic model-data integration to quantify the climatic impacts of nature-based solutions and inform decision-making in farming practice, policy design, and economic returns.

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

This session covers climate predictions from seasonal to multi-decadal timescales and their applications. Continuing to improve such predictions is of major importance to society. The session embraces advances in our understanding of the origins of seasonal to decadal predictability and of the limitations of such predictions. This includes advances in improving forecast skill and reliability and making the most of this information by developing and evaluating new applications and climate services.
The session welcomes contributions from dynamical models, machine-learning or other statistical methods and hybrid approaches. It will investigate predictions of various climate phenomena, including extremes, from global to regional scales, and from seasonal to multi-decadal timescales (including seamless predictions). Physical processes and sources relevant to long-term predictability (e.g. ocean, cryosphere, or land) as well as predicting large-scale atmospheric circulation anomalies associated with teleconnections will be discussed. Analysis of predictions in a multi-model framework, and ensemble forecast initialization and generation will be another focus of the session. We are also interested in approaches addressing initialization shocks and drifts. The session welcomes work on innovative methods of quality assessment and verification of climate predictions. We also invite contributions on the use of seasonal-to-decadal predictions for risk assessment, adaptation and further applications.