The science-policy interface is not just as a way to increase the impact of our science, but it is also a scientific subject in itself. It presents several challenges to both scientists and policy-makers. They include understanding the different steps in the policy cycle: from setting the agenda to formulating, adopting, implementing, monitoring and evaluating polices. It is also crucial to know which facts and evidences are most needed at each step, so scientists can provide the best information at the right time and in the best way.

This session provides the opportunity for discussing with policy makers and addressing the necessary skills to facilitate the uptake of hydrological sciences in policy formulation and implementation.

This session will host invited-talks only and an interactive online/onsite panel discussion with the audience.

Liaising with stakeholders, policy-makers and society is becoming increasingly important for academic research to turn research into impactful action, but also to improve research by allowing society to take part within research processes in terms of co-producing knowledge and policy. In hydrological sciences, this is needed when implementing innovative solutions in areas such as river basin management, water allocation, impact-based hydrological forecasting, flood protection, drought risk management, climate change mitigation, ecohydrology and sustainable environmental solutions, among others.
Contributions focus on:
1. Science-policy interface in hydrology. How science influences policy and policies impact science? How scientists can provide easily digestible pieces of evidence to policy-makers? What are the key gaps in joining science to feasible policy solutions in the water sector? How can we use knowledge to improve policy, and vice-versa? How do we deal with uncertainty, adaptation, path dependencies but also with aspects of power, inequality and vested interests in the co-production of knowledge and policy?
2. Interdisciplinary collaborations. How do we create the interdisciplinary knowledge needed to address the questions faced by decision-makers and societal stakeholders? How have new, interdisciplinary, science questions been generated in response to existing and emerging research problems? How can individual disciplinary perspectives come together in interdisciplinary studies and experiments?
3. Hydrology as practiced within society. Who are the users of our knowledge, how useful is our knowledge for those societal users, how useful are our tools, models and methods? What approaches are available to support a fruitful collaboration between hydrological science and practitioners? And, since scientists are not removed from the things they study, how has hydrological science been shaped by the historical interplay of cultural, political and economic factors? What are the opportunities and challenges that this science/society nexus creates for producing scientific knowledge?

4. Understanding of complex human-water systems and their management: what are the feedback mechanisms of emergent phenomena in human-water systems? What are the benefits and shortcomings based on empirical, conceptual or model-based research and disciplinary perspective? How can we enable stakeholders to avoid unintended consequences of water management decisions?

This session welcomes abstracts that consider how to observe, model and analyse interactions of people and water, and the effects of social and environmental changes on hydrological systems. It is organised as part of the IAHS Panta Rhei hydrological decade 2013-2022; and focuses on gains in our understanding of dynamic human-water systems.
Examples of relevant areas include:

- Observations of human impacts on, and responses to, hydrological change.
- Interactions of communities with local water resources.
- Hydrological models that include anthropogenic effects.
- Creation of databases describing hydrology in human-impacted systems.
- Data analysis and comparisons of human-water systems around the globe and especially in developing and emerging countries.
- Human interactions with hydrological extremes, i.e. floods and droughts, and water scarcity.
- The role of gender, age, and cultural background in the impacts of hydrological extremes (floods and droughts), risk perception, and during/after crises and emergencies.
- innovative modelling for exploring the interplay, feedback, and interactions between hydrological extremes and public and private adaptation actions;
- integration of models and observations for advancing knowledge on the human-water systems;
- new frameworks to support risk-based decision-making in case of multi-hazards;

Groundwater, the hidden component of the water cycle, traditionally receives less attention than surface water from both the scientific community and policy makers, due to it being "out of sight, out of mind". However, this precious resource is inextricably linked to the maintenance of natural ecosystems and human well-being. Groundwater has always been part of the lives of worldwide communities: irrigated agriculture is primarily sustained by groundwater resources, particularly in arid and semi-arid regions; holy wells and sacred springs are part of our global cultural heritage, while disagreement over groundwater resources have previously resulted in turmoil and national/transboundary conflicts. These obvious interconnections, however, are neglected in favour of the development of sectorial approaches to groundwater resource assessment.
Socio-hydrogeology has recently been proposed as an effective approach to addressing complex groundwater-related issues in an increasingly holistic and integrated manner. By focusing on the reciprocity between humans and groundwater, it aims to explore and understand their dynamic interactions and feedbacks with a final goal of developing transdisciplinary solutions for transdisciplinary problems. Due to the more "personal" (i.e., individual household/community supplies) and local nature of groundwater in many instances, socio-hydrogeology seeks to understand individuals and communities as a primary source, pathway and receptor for potable groundwater supplies, including the role of local knowledge, beliefs, risk perception, tradition/history, and consumption. In essence, the “socio” in socio-hydrogeology embodies sociology, including social, cognitive, behavioural and socio-epidemiological science.

For this session we encourage contributions from diverse fields, including:
• Examples of socio-hydrogeological assessments (e.g., participatory monitoring, stakeholder engagement, public participation, citizen science)
• Integration of “non-expert” knowledge and experience within quantitative and qualitative hydrogeological studies
• Challenges and opportunities arising from the integration of hydrogeology and social sciences
• Social and political approaches to water resources research
• Groundwater geoethics and national/transboundary conflicts
• Attempts to integrate behavioural, experiential or knowledge-based data with hydrogeological/health risk assessment models
• Educational goals for future socio-hydrogeologists

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.

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.

Many papers have advised on carefully considering the methods we choose for our modelling studies as they potentially affect our modelling results and conclusions. However, there is no common and consistently updated rulebook on what good modelling practice is and how it has evolved since e.g. Klemes (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, none of the proposed methods have become quite as common and indispensable as the split sample test (KlemeŠ, 1986), despite their very justified existence.

This session hopes to provide a platform for a visible and ongoing discussion on what ought to be the current standard for an appropriate modelling protocol to acquire robust and reliable results considering uncertainty in all its facets. We aim to bring together, highlight and foster work that applies, develops, or evaluates procedures for a robust modelling workflow or that investigates good modelling practices. 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
(6) Investigating subjectivity along the modelling chain
(7) Uncertainty propagation along the modelling chain
(8) Communicating model results and their uncertainty to end users of model results
(9) Evaluating implications of model limitations and identifying priorities for future model development and data acquisition planning

This session focuses on advances in theoretical, methodological and applied studies in hydrologic and broader earth system dynamics, regimes, transitions and extremes, along with their physical understanding, predictability and uncertainty, across multiple spatiotemporal scales.

The session further encourages discussion on interdisciplinary physical and data-based approaches to system dynamics in 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.

Contributions are gathered from a diverse community in hydrology and the broader geosciences, working with diverse approaches ranging from dynamical modelling to data mining, machine learning and analysis with physical process understanding in mind.

The session further encompasses practical aspects of working with system analytics and information theoretic approaches for model evaluation and uncertainty analysis, causal inference and process networks, hydrological and geophysical automated learning and prediction.

The operational scope ranges from the discussion of mathematical foundations to development and deployment of practical applications to real-world spatially distributed problems.

The methodological scope encompasses both inverse (data-based) information-theoretic and machine learning discovery tools to first-principled (process-based) forward modelling perspectives and their interconnections across the interdisciplinary mathematics and physics of information in the geosciences.

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.

Eric Wood passed away November 3, 2021. His career spanned five decades. It included early work in systems analysis applications to hydrology dating to his dissertation research at MIT in the 1970s, scaling in the 1980s and 1990s, hydrologic remote sensing beginning with planning for NASA’s Earth Observing System in the 1980s and 1990s, continental hydrology beginning in the 1990s, and hyper-resolution land surface modeling in the mid-2000s, with a "call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort" and face this "grand challenge" [1]. A hallmark of Eric's career was strong international collaborations, especially with European scientists, notably with his most recent contribution to the development of the End-to-end Demonstrator for improved decision-making in the water sector in Europe (EDgE) for the Copernicus Climate Change Service [2]. Eric Wood attended almost all previous EGU meetings (most recently, the GA in 2019), and was awarded the 2007 John Dalton Medal of the Hydrological Sciences division, and the Union's 2014 Alfred Wegener Medal & Honorary Membership. This session will review Eric's main contributions to hydrology, from data to models, highlighting the experience of former students, postdocs, and colleagues that his life touched.

[1] Wood et al.: Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water; https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2010WR010090
[2] Samaniego et al.: Hydrological Forecasts and Projections for Improved Decision-Making in the Water Sector in Europe; https://journals.ametsoc.org/view/journals/bams/100/12/bams-d-17-0274.1.xml

Water is a strategic issue in the African and Mediterranean regions, mainly because of the scarcity of the available resources in quantity and/or quality. The Mediterranean and African climates and the surface hydrology are characterized by a strong variability in time and space and the importance of extreme events droughts and floods. During the last century, changes of all kinds and intensities, including in the agricultural sector have affected surface and underground reservoirs and water uses. Global and regional hydrological models have recently seen tremendous advances in improved representations of physical processes underpinning these impacts, resulting in better reproductions of observed variables such as streamflow and water extent. As a result, they are increasingly used for predicting socio-economic risks of floods, droughts and water stress in regions around the globe. However, the use of hydroclimatic models for disaster risk reductions in data-sparse regions, while gradually improving, is still limited in comparison.

This session intends to identify and analyse the changes in the Mediterranean and Africa hydrology, in terms of processes, climate and other water-related topics, including environmental and food security. It will gather specialists in observation and modelling of the various water fluxes and redistribution processes within the catchments. Case studies showcasing practical experiments and innovative solutions in decision making under large uncertainty are ncouraged. Contributions addressing the following topics are welcome:

• Spectacular case studies of rapid changes in water resources;
• Using various sources of information for comparing past and present conditions;
• Differentiating climatic and anthropogenic drivers (including GCM reanalysis);
• Modelling hydrological changes (in surface and/or ground water);
• Impacts of extreme events on water systems.

Forests are recognized as prime regulators of the hydrological cycle. Changes in their structure cause effects on the ecosystem services they provide via their water and biochemical cycles. The traditional idea that forest hydrology emphasizes the role of forests and forest management practices on runoff generation and water quality has been broadened in light of rapid global change. Some of the largest pristine forested areas are in the tropics and have suffered drastic land-use changes during recent decades. These tropical systems are still markedly underrepresented in hydrological studies, especially concerning long-term experimental setups and monitoring networks.

Anthropogenic intervention is exerting ever-increasing pressure on natural ecosystems, affecting water quantity and quality, and threatening socio-economic and human development as described by the UN Sustainable Development Goals. Yet, we lack a proper understanding of how catchments respond to changing environmental conditions and disturbances. Answering these open questions requires interdisciplinary approaches in combination with novel monitoring methods and modelling efforts. This session brings together studies that will enhance our understanding and stimulate discussions on the impact of global change on hydrological processes in forest systems at different scales.

We invite field experimentalists and modellers to submit contributions investigating hydrological processes in forests from boreal to tropical regions, including water quality, the carbon cycle, or ecohydrological aspects.

This session welcomes studies that:
1) Improve our understanding of hydrological processes in forested catchments and the resilience of forested catchments to environmental changes and disturbances;
2) Assess the hydrological-related impacts of land use/cover change on forested systems;
3) Present new methods (e.g. remote sensing techniques) or tools that unveil new perspectives or data sources in forest hydrology;
4) Include interdisciplinary research that holistically integrates data and models from soil–plant–atmosphere experimental or modelling schemes into hydrological studies.

Despite only representing about 25% of continental land, mountains are an essential part of the global ecosystem and are recognised to be the source of much of the world’s surfaces water supply apart from important sources of other commodities like energy, minerals, forest and agricultural products, and recreation areas. In addition, mountains represent a storehouse for biodiversity and ecosystem services. People residing within mountains or in their foothills represent approximately 26% of the world’s population, and this percentage increases to nearly 40% when considering those who live within watersheds of rivers originated in a mountain range. This makes mountains particularly sensitive to climate variability, but also unique areas for identifying and monitoring the effects of global change thanks to the rapid dynamics of their physical and biological systems.
This session aims to bring together the scientific community doing hydrology research on mountain ranges across the globe to share results and experiences. Therefore, this session invites contributions addressing past, present and future changes in mountain hydrology due to changes in either 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 for this session are:
• Sources of information for evaluating past and present conditions (in either surface and/or ground water 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.

Water stored in the snow pack 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 snow to rain, earlier snowmelt, and a decrease in peak snow accumulation) will reflect both on water resources availability and water uses at multiple scales, with potential implications for energy and food production.

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 large spatial variability of hydrological and weather data in such areas. This translates into limited process understanding, especially in a warming climate.

This session aims at bringing together those scientists that define themselves to some extent as cold region hydrologists, as large as this field can be. Contributions addressing the following topics are welcome:
- Experimental research on snow-melt & 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 on cryosphere-influenced mountain hydrology, such as landforms at high elevations and their relationship with streamflow, water balance of snow/ice-dominated mountain regions;
- Studies addressing the impact of climate change on the water cycle of snow and ice affected catchments.

Large data samples of diverse catchments can provide insights into relevant physiographic and hydroclimatic factors that shape hydrological processes. Further, large data sets increasingly cover a wide variety of hydrologic conditions, enabling the development of several research topics, such as extreme events, data and model uncertainty, hydrologic model evaluation and prediction in ungauged basins.
This session aims to showcase recent data and model-based efforts on large-sample hydrology, which advance the characterization, organization, understanding and modelling of hydrological diversity. We specifically 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 unequal geographical representation of catchments, quantification of uncertainty, catchment heterogeneities and human interventions for fair comparisons among datasets?
2. Catchment similarity and regionalization:
Can currently available global datasets be used to define hydrologic similarity? How can information be transferred between catchments?
3. Modelling capabilities:
How can we improve hydrological modelling by using large samples of catchments?
4. Testing of hydrologic theories:
How can we use large samples of catchments to transfer hydrologic theories from well-monitored to data-scarce catchments?
5. Identification and characterization of dominant hydrological processes:
How can we use catchment descriptors available in large sample datasets to infer dominant controls for relevant hydrological processes?
6. Human impacts and non-stationarity
How can we use large samples of catchment data to infer hydrological response under changing environmental conditions?

A splinter meeting is planned to discuss and coordinate the production of large-sample data sets, entitled “Large sample hydrology: facilitating the production and exchange of data sets worldwide”. See the final programme for location and timing.

The session and the splinter meeting are organized as part of the Panta Rhei Working Group on large-sample hydrology.

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.

The application of multi-datasets and multi-objective functions has proven to improve the performance of hydrologic and water quality models by extracting complementary information from multiple data sources or multiple features of modelled variables. This is useful if more than one variable (runoff and snow cover, sediment, pollutant concentration, or stable isotope) or more than one characteristic of the same variable (e.g., flood peaks and recession curves) are of interest. Similarly, a multi-model approach can overcome shortcomings of individual models, while testing a model at multiple scales using a large sample of catchments helps to improve our understanding of the model functioning in relation to catchment processes. The use of multiple data sources in data-driven approaches can help engineering data-driven models with higher predictability skills. Finally, the quantification of multiple uncertainty sources enables the identification of their contributions and this is critical for uncertainty reduction and decision making under uncertainty.
This session welcomes contributions that apply one or more of the multi-aspects in hydrological, ecological and water quality studies. In particular, we seek studies covering the following issues:
• Frameworks using multi-objective or multi-variables to improve the identification (prediction) of hydrological, ecological or water quality models;
• Studies using multi-model or multiple-data-driven approaches;
• Use of multiple scales, sites or large-sample studies to improve understanding of catchment processes;
• Assimilation of remote sensed data or use of multi-datasets to improve model identification;
• Hypothesis testing with one of the multi-aspects
• Metaheuristics (e.g., Monte Carlo) or Bayesian approaches in combination with multi-aspects of model identification;
• Techniques to optimize model calibration or uncertainty quantification via multi-aspect analyses;
• Studies handling multiple uncertainty sources in a modelling framework.
• Application of machine learning and data mining approaches to learn from large, multiple or high-resolution data sets.

The importance of soil moisture for the hydrological systems dynamics is undebated. A great deal of observations and research have been invested in the last decades to improve the knowledge of soil water status as well its spatial and temporal variation within a given hydrological system. In that effort, several types of soil moisture data have become available, spanning from in-situ observations, radar data, cosmic ray studies to several satellite products.

Although spatial and temporal patterns of soil moisture are the result of processes that hydrological models typically capture, the application of the currently available soil moisture information for improving models is progressing only slowly. This is partly due to a gap between the information content provided by the available data and the information required to improve models. Furthermore, some essential parts of soil water storage at the larger scale, like that of the root zone, is typically assessed using combination of models and data, resulting in a lack of independent information for validation.

This session invites contributions dealing with closing these gaps. This could, for example, be achieved by progress in the descriptions of the processes causing the spatial and temporal variations in soil moisture or by more efficiently using information from available data to improve model predictions across scales. The session is explicitly open for research across all relevant hydrological scales: local, hillslope, catchment up to the continental scale, and deal with both the vertical and lateral flow processes.

Examples for suitable contributions are (but are not limited to):
- The role of soil moisture in the functioning of hydrological systems
- Methods and case studies on improving the predictive power of models using soil moisture data
- Deriving process knowledge from soil moisture data that can be used to improve hydrological models
- Evaluating the suitability of given soil moisture data types for representing hydrologic processes

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 have 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 to aquatic ecology.
Models can help to optimize monitoring schemes and provide assessments of future change and management options. However, insufficient temporal and/or spatial resolution, a short duration of observations and the widespread use of different analytical methods restrict the data base 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. Additionally, models should be capable of representing changing land use and climate conditions, which is a prerequisite to meet the increasing needs for decision making. The strong need for advances in water quality models remains.

This session aims to bring scientist together who work on experimental as well as on modelling studies to improve the prediction and management of water quality constituents (nutrients, organic matter, algae, or sediment) at the catchment scale. Contributions are welcome that cover the following issues:

- 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 efficient water quality monitoring schemes
- Innovative monitoring strategies that support both process investigation and model performance
- Advanced modelling tools integrating catchment as well as in-stream processes
- Observational and modelling studies at 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

Water quantity and quality is typically assessed and managed at the scales of catchments and aquifers. However, flow and transport integrate a multitude of hydrological transport and biogeochemical reaction processes interacting at different temporal and spatial scales, and thus hampering the understanding of underlying cause-effect relationships.
Recent advances in high-frequency measurements, machine learning, and the use of age tracers and their modelling have enhanced process understanding of flow and transport in catchments and aquifers. Our session brings together studies approaching this challenge from different angles and with different tools:
- Data-driven interpretation of water quality time series observed at the catchment outlet
- Isotope- and model-driven evaluation of transit times and water ages in catchments including the groundwater compartment
- Linkages of water transit times, hydrochemical and ecohydrological response

Stable and radioactive isotopes as well as other natural and artificial tracers are useful tools to fingerprint the source of water and solutes in catchments, to trace their flow pathways or to quantify exchanges of water, solutes and particulates between hydrological compartments. Papers are invited that demonstrate the application and recent developments of isotope and other tracer techniques in field studies or modelling in the areas of surface / groundwater interactions, unsaturated and saturated zone, rainfall-runoff processes, nutrient or contaminant export, ecohydrology or other catchment processes.

The occurrence of pathogens and 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) are introduced into surface water through the direct discharge of wastewater, or by the release from animal manure or animal waste via overland flow or groundwater, 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 or as discharges from wastewater treatment plants (e.g., trace organic contaminants). 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. Consequently, we welcome contributions that aim to close these knowledge gaps and include both small and large-scale experimental and modelling studies with a focus on:
- The development and application of novel experimental and analytical methods to investigate fate and transport of fecal indicators, pathogens and emerging contaminants in rivers, groundwater and estuaries
- Hydrological, physically based modelling approaches
- Methods for identifying the dominant processes and for transferring fecal indicator, pathogen and contaminant transport parameters 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

A large number of pathogens, micropollutants and their transformation products (veterinary and human pharmaceuticals, personal care products, pesticides and biocides, chlorinated compounds, PFAS, 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 programmes 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 ground- 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 and pathogens in the soil-groundwater-river continuum.

Topics cover:
- Novel sampling and monitoring concepts and devices
- New analytical methods, new detection methods for DNA, pathogens, micropollutants, non-target screening
- Experimental studies and modelling approaches to quantify diffuse and point source inputs
- Novel monitoring approaches such as non-target screening as tools for improving processes understanding and source identification such as industries
- Comparative fate studies on parent compounds and transformation products
- Diffuse sources and (re-)emerging chemicals
- Biogeochemical interactions and impact on micropollutant behaviour
- Setup of mitigation measures and evaluating their effectiveness.

Plastic pollution in freshwater systems is a widely recognized global problem with potential environmental risks to water and sediment quality. 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.
In this session, we explore the current state of knowledge and activities on macro-, micro- and nanoplastics in freshwater systems, including aspects such as:
• Plastics in rivers, lakes, urban water systems, floodplains, estuaries, freshwater biota;
• Monitoring and analysis techniques;
• 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);
• Transport processes of plastics at catchment and local scale;
• The role of river regulation structures, e.g. dams, navigation, flood control, etc., in plastic retention and transport
• Effects of hydrological extremes, e.g. accumulation of plastics during droughts, and short-term export during floods in the catchment;
• Degradation and fragmentation processes, e.g. from macro- to micro- and nanoplastics;
• Modelling approaches for local and/or global river output estimations;
• Legislative/regulatory efforts, such as monitoring programs and measures against plastic pollution in freshwater systems.

Bayesian approaches have become increasingly popular in water quality modelling, thanks to their ability to handle uncertainty comprehensively. This is particularly relevant in environmental decision making where Bayesian inference enables to consider the reliability of predictions of the consequences of decision alternatives, alongside uncertainties related to decision makers’ risk attitudes and preferences, uncertainty related to system understanding and random processes. Graphical Bayesian Belief Networks and related approaches (hierarchical models, ‘hybrid’ mechanistic/data-driven models) can be particularly powerful decision support tools that make it relatively easy for stakeholders to engage in the model building process and inform adaptive water quality management within an uncertainty framework. The aim of this session is to review the state-of-the-art in this field and compare software and procedural choices to consolidate and set new directions for the emerging community of Bayesian water quality modellers. Building on past three years’ success of this session, a specific new emphasize for this year’s session is to explore the utility of Bayesian water quality models in supporting decision making.

We seek contributions from water quality research that use Bayesian approaches to, for example but not exclusively:
• involve stakeholders in model development and maximise the use of expert knowledge
• integrate prior knowledge, especially problematizing the choice of Bayesian priors
• inform risk analysis and decision support using diverse data and evidence
• represent the preferences of the stakeholders in the form of value functions through elicitation, and account for the uncertainty in preferences
• produce accessible decision support tools
• model water quality in data sparse environments
• compare models with different levels of complexity and process representation
• quantify the uncertainty of model predictions (due to data, model structure and parameter uncertainty)
• address the problem of scaling (e.g. disparity of scales between processes, observations, model resolution and predictions) through hierarchical models
• quantify especially model structural error through, for example, Bayesian Model Averaging or structural error terms
• use statistical emulators to allow probabilistic predictions of complex modelled systems
• use machine-learning and data mining approaches to learn from large, possibly high-resolution data sets.

In the current context of global change, assessing the impact of climate variability and changes on hydrological systems and water resources is increasingly crucial for society to better-adapt to future shifts 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, whose contribution to near-future changes could be as important as forced anthropogenic climate changes at the regional scales. Internal climate modes of variability (e.g. ENSO, NAO, AMO) and their impact on the continent are not always properly reproduced in the current global climate models, leading to large underestimations of decadal climate and hydro-climatic variability at the global scale. At the same time, hydrological response strongly depends on catchment properties, whose interactions with climate variability are little understood at the decadal timescales. These factors altogether significantly reduce our ability to understand long-term hydrological variability and to improve projections and reconstructions of future and past hydrological changes upon which improvement of adaption scenarios depends.

We welcome abstracts capturing recent insights for understanding past or future impacts of large-scale climate variability on hydrological systems and water resources as well as newly developed projection and reconstruction scenarios. Results from model intercomparison studies are encouraged.

This session focusses on hydrological response to changes in climatic forcing at multi-annual to multi-decadal timescales. Catchments are immensely complex and unique systems responding to external factors (e.g. changes in climate) on a variety of timescales due to complex interactions and feedbacks between their components. Recent evidence suggests a tendency for existing models and methods to downplay the impact of a given climatic change on streamflow with major implications for the reliability of such methods for future planning. The poor performance of models suggests they potentially misrepresent (or omit) important catchment processes, process timescales, or interactions between processes. The multitude of responses and feedbacks developing in the critical zone need to be disentangled and understood to improve our ability to make hydrological predictions under different and continuously changing climatic conditions.

We invite submissions on themes such as (but not limited to):
1. Better understanding of hydrological and/or biophysical processes related to long-timescale climate shifts potentially contributing to apparent shifts in hydrologic response;
2. Understanding and quantifying catchment multi-annual “memory”
3. Modelling studies aiming to evaluate and/or improve hydrologic simulations under historic climatic variability and change;
4. Efforts to improve the realism of runoff projections under future climate scenarios;
5. Studies that explore implications of long term-hydrologic change for water availability, risk, or environmental outcomes including interactions with human factors such as landuse changes, evolving water policy, and management intervention.

The space-time dynamics of floods are controlled by atmospheric, catchment, river system and anthropogenic processes and their interactions. The natural oscillatory behaviour of floods (between flood-rich and flood-poor periods) superimpose with anthropogenic climate change and human interventions in river morphology and land uses. In addition, flood risk is further shaped by continuous changes in exposure and vulnerability. Despite more frequent exploratory analyses of the changes in spatio-temporal dynamics of flood hazard and risk, it remains unclear how and why these changes are occurring. The scope of this session is to report when, where, how (detection) and why (attribution) changes in the space-time dynamics of floods occur. Of particular interest is what drivers are responsible for observed changes. Presentations on the impact of climate variability and change, land use changes and morphologic changes in streams, as well as on the role of pre-flood catchment conditions in shaping flood hazard and risk are welcome. Furthermore, contributions on the impact of structural measures and demographic and socio-economic factors on past and future risk changes are invited. This session is jointly organised by the Panta Rhei Working Groups “Understanding Flood Changes” and “Changes in Flood Risk”. The session will further stimulate scientific discussion on flood change detection and attribution. Specifically, the following topics are of interest for this session:
- Decadal oscillations in rainfall and floods
- Process-informed extreme value statistics
- Interactions between spatial rainfall and catchment conditions shaping flood patterns
- Detection and attribution of flood hazard changes: atmospheric drivers, land use controls and river training, among others
- Changes in flood risk: urbanisation of flood prone areas; implementation of multi-scale risk mitigation measures, such as natural water retention measures and private precautionary measures; changes of economic, societal and technological aspects driving flood vulnerability and damages, among others.
- Future flood risk scenarios and the role of adaptation and mitigation strategies

Hydrological extremes (floods and droughts) have major impacts on society and ecosystems and are posited to increase in frequency and severity with climate change. These events at the two ends of the hydrological spectrum are governed by different processes, which means that they operate on different spatial and temporal scales and that different approaches and indices are needed to characterise them. However, there are also many similarities and links between the two types of extremes that 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 increase the understanding of the governing processes of both types of hydrological extremes, find robust ways of modelling and analysing floods and droughts, 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 analysis of flood or drought non-stationarity under the effects of climate-, land cover-, and other anthropogenic changes. These might include storyline and stress testing approaches to better understand hydrological responses under changed (extreme) conditions. Studies that investigate both types of extremes are of particular interest. Submissions from early-career researchers are especially encouraged.

Large-scale hydrological research is very important in many different contexts - examples include: increase understanding of the climate system and water cycle, assessment of water resources in a changing environment, hydrological forecasting, and 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) use of global earth observations and in-situ datasets for large scale hydrology and data assimilation techniques for large scale hydrological models;

(iii) understanding and modelling of extremes: like droughts and floods;

(iv) representing and evaluating different components of the terrestrial water cycle fluxes and storages (e.g. soil moisture, snow, groundwater, lakes, floodplains, evaporation, river discharge) and their impact on current and future water resources and atmospheric modelling;

(v) synthesis studies assembling knowledge gained from smaller scales (e.g. catchments or hillslope) to advance our knowledge on process understanding needed for the further development of large-scale models and to identify large-scale patterns and trends.

Since early work on the assessment of global, continental and regional-scale water balance components, many studies use different approaches including global models, as well as data-driven approaches that ingest in-situ or remotely sensed observations or combinations of these. They attempted to quantify water fluxes (e.g. evapotranspiration, streamflow, groundwater recharge) and water storage on the terrestrial part of the Earth, either as total estimates (e.g. from GRACE satellites) or in separate compartments (e.g. water bodies, snow, soil, groundwater). In addition, increasing attention is given to uncertainties that stem from forcing datasets, model structure, parameters and combinations of these. Current estimates in literature show that flux and storage estimates differ considerably due to the methodology and datasets used such that a robust assessment of global, continental and regional water balance components remains challenging.

This session is seeking for contributions focusing on:
i. past/future assessment of water balance components (fluxes and storages) such as precipitation, freshwater fluxes to the oceans (and/or inland sinks), evapotranspiration, groundwater recharge, water use, changes in terrestrial water storage or individual components at global, continental and regional scales,
ii. application of innovative explorative approaches undertaking such assessments – through better use of advanced data driven, statistical approaches and approaches to assimilate (or accommodate) remote sensing datasets for improved estimation of terrestrial water storages/fluxes,
iii. analysis of different sources of uncertainties in estimated water balance components,
iv. examination and attribution of systematic differences in storages/flux estimates between different methodologies, and/or
v. applications/consequences of those findings such as sea level rise and water scarcity.

We encourage submissions using different methodological approaches. Contributions could focus on any of the water balance components or in an integrative manner with focus on global, continental or regional scale applications. Assessments of uncertainty in past/future estimates of water balance components and their implications are highly welcome.

Groundwater provides about 40% of all human water abstractions and is an essential water source for freshwater biota in rivers, lakes, and wetlands. Aquifers may span political and natural boundaries, but our large-scale understanding of groundwater processes and their interconnection to surface water is still limited.
Increasingly global-scale groundwater models are being developed, and big-data assessments of groundwater wells have been conducted to push the boundaries of our large-scale understanding of groundwater processes. Similar to the catchment scale, knowledge of the exchange between surface and subsurface waters is essential for determining the hydrological water balance at larger scales. Furthermore, surface and subsurface waters exchanges, as well as 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) could alter the natural conditions for the groundwater flow processes and exchange between surface and subsurface.
In this session, we want to highlight the increasing interest in the large-scale study of groundwater availability and processes while discussing current obstacles related to data availability and model design. Therefore, we seek contributions addressing issues including:
• Regional to global groundwater-related datasets and big-data assessments
• Transboundary and inter-catchment assessments of groundwater processes
• Surface-subsurface water exchange at the catchment to global scales from both observational and modeling aspects
• Effects of surface-subsurface water exchange on hydrological extremes (drought/flood), water availability, and solute and pollutant transport under climate change
• Implications of large-scale groundwater understanding on monitoring design and integrated water management beyond the catchment scale
• Variation of controls on groundwater processes across large domains

Hydroinformatics has emerged over the last decades to become a recognised and established field. It is concerned with the development and hydrological application of mathematical modelling, ICT, systems science and computational intelligence tools. We also have to face the challenges of Big Data: large data sets, both in size and complexity.

The aim of this session is to provide an active forum in which to demonstrate and discuss the integration and appropriate application of emergent computational technologies in a hydrological modelling context. Topics of interest are expected to cover a broad spectrum of theoretical and practical activities that would be of interest to hydro-scientists and water-engineers. The main topics will address the following classes of methods and technologies:

* Methods for the analysis of complex data sets, including remote sensing and crowdsourced data
* Clustering algorithms: hard vs fuzzy clustering, comparison of methods, alternative clustering methods (sequential, evolutionary, deep, ensemble, etc.)
* Predictive and analytical models based on the methods of statistics, computational intelligence, machine learning and data science: neural networks, deep learning techniques, fuzzy systems, genetic programming, chaos theory, etc.
* Specific concepts and methods of Big Data and Data Science
* Optimisation methods associated with heuristic search procedures: various types of genetic and evolutionary algorithms, randomised and adaptive search, etc.
* Applications of systems analysis and optimisation in water resources
* Hybrid modelling involving different types of models both process-based and data-driven, combination of models (multi-models), etc.
* Data assimilation and model reduction in integrated modelling
* Novel methods of analysing model uncertainty and sensitivity
* Demonstrating the benefit of the use of Citizen Observatories, crowdsourcing, and innovative sensing techniques for monitoring, modelling, and management of water resources
* Software architectures for integrating different types of models and data sources

Applications could belong to any area of hydrology or water resources: rainfall-runoff modelling, flow forecasting, sedimentation modelling, analysis of meteorological and hydrologic data sets, linkages between numerical weather prediction and hydrologic models, model calibration, model uncertainty, optimisation of water resources, etc.