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 and addressing the necessary skills to facilitate the uptake of hydrological sciences in policy formulation and implementation. We will discuss expectations, actual practice, research challenges and the skills that enable (or prevent) advances in the field.

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

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 finalisation and synthesis activities of the IAHS Panta Rhei hydrological decade 2013-2023; and focuses on gains in our understanding of dynamic human-water systems.
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.
- 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.

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.

Hydrology training, education and teaching is central to advancement of hydrological sciences, practice and policy. This session aims to revive the earlier discussions on hydrology education while taking a fresh perspective on the transformative principles and approaches required in a new era of advanced technology, knowledge generation and science governance. The transition to online education (during the covid-19 lockdown), the rising interdisciplinary nature of hydrology as well as greater support for open as well as citizen science emphasises the need for hydrologists to adapt their teaching and learning processes. These include curriculum development, design of hybrid teaching formats (e.g., online field trips), inclusion of coding and laboratory experiments in classes, creating open educational resources and tools, testing new examination methods, and transdisciplinary learning. With increasing scope and responsibility of teaching, there is also greater interest in teaching as an academic career path. Overall, it is high time that the hydrology community take steps towards envisioning a better future for hydrology education. To this end, our session gives the opportunity for a joint dialogue between teaching enthusiasts. We invite contributions, especially by early career scientists, that share experiences (e.g., lessons learned, best practices), offer critical perspectives (e.g., the need for a new hydrology textbook) or discuss future ways forward (e.g., establishing more BSc degrees in hydrology).

We will start off with the solicited presentation by Christopher Skinner (virtual). Next, the first half will be dedicated to on-site poster presentations (5 min/poster) with a kickoff tour guided by conveners (random visitors can join whenever they do); while the second half will be for a virtual component on gather.town.

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.

The MacGyver session this year teams up with the Frontiers in river flow monitoring session. The 'author in attendance' blocks are in the early morning and late afternoon. In between those two block we organize a field session with hands-on on different state of the art hydrometry techniques. Bring your own measurement system and show case it, or join us to see others demonstrate their devices! Details on this field trip:

Monday, 24th of April, 10:30 to 16:00 hrs
Departure by bus at 10:30 hrs from AVC Center
Platz der Vereinten Nationen close to underground station Kaisermühlen VIC
Lunch and beverages will be provided

If you are interested please send us an email: pena@photrack.ch

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 river flow methods and which link innovative research to operational monitoring.

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. 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, 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 along the modelling chain
(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

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.

Water is a strategic issue in the Mediterranean region, mainly because of the scarcity of the available resources, in quantity and/or quality. The Mediterranean climate and the surface hydrology are characterized by a strong variability in time and space and the importance of extreme events, droughts and floods. This irregularity is also met at a lower level in aquifers dynamics. During the last century, modifications of all kinds and intensities have affected surface conditions and water uses. The Mediterranean hydrology is then continuously evolving.

This session intends to identify and analyse the changes in the Mediterranean hydrology, in terms of processes, fluxes, location. It will gather specialists in observation and modeling of the various water fluxes and redistribution processes within the catchments.
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.

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 in the region. The advances seen in hydrological 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 reductions still requires improvement.

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 and mapping, seasonal forecasting, water resources management, climate impact assessment and societal implications. Interdisciplinary studies that combine the physical drivers of water-related risks and their socio-economic impacts in Africa are encouraged. Case studies showcasing practical innovative solutions relevant for decision making under large uncertainty are welcomed.

Water is the main influencing factor for life in drylands. Dryland ecosystems and their inhabitants strongly rely on the scarce and often intermittent water availability in these regions. Drylands' characteristics make them more vulnerable to climate variability and more susceptible to the impact of extreme events. These events can reshape the landscape through the mobilisation of surface sediments and forming sedimentary deposits, which preserve and allow the reconstruction of past states of the Earth's system, including changes in the extent of deserts. Nevertheless, the study of hydroclimatic processes in drylands remains at the periphery of many geoscientific fields. A proper understanding of the hydrological, hydrometeorological and climatic processes in these regions is a cornerstone to achieve the proposed sustainable development goals we set for the end of this century.

This session brings together scientific disciplines addressing drylands' full range of environmental and water-related processes. The purpose is to foster interdisciplinary research and expand knowledge and methods established in individual subdisciplines.

Forests primarily regulate 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. Some of the largest pristine forest areas are in the tropics and have undergone drastic changes in land use in recent decades. Although novel modeling and observational techniques have been applied as alternatives to develop cutting-edge research, these tropical systems remain notably underrepresented in hydrological studies compared to temperate regions, especially concerning long-term experimental setups and monitoring networks.
Improving our understanding of how hydrological processes in the forest are determined by time-invariant factors and time-varying controls, as well as how forest catchments respond to dynamic environmental conditions and disturbances, will depend critically on understanding forest-water interactions. Building this knowledge requires interdisciplinary approaches in combination with new monitoring methods and modeling efforts.
This session brings together studies that will improve our understanding and stimulate debate on the impact of global change on hydrological processes in forest systems 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 systems;
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.

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 (systematically) represent human influences in large sample datasets and use them 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.

A multitude of processes contribute to the hydrologic function of catchments. Traditionally, catchment hydrology has been centered around surface runoff, which is readily observable. At the same time, belowground processes, including subsurface runoff, as well as feedbacks to the surface and the specific role of soil moisture in shaping these fluxes is still underexplored. This session is dedicated specifically to
• identify and model subsurface runoff generation at the catchment scale
• improve and validate representation of feedbacks between surface and subsurface processes in models
• how soil moisture measurements across scales are used to improve process understanding, models and hydrological theory

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 their flow pathways or (iii) to quantify exchanges of water, solutes and particulates between hydrological compartments. We invite contributions that demonstrate the application and recent developments of isotope and other tracer techniques in hydrological field studies or modelling in the areas of surface/groundwater interactions, unsaturated and saturated zone, rainfall-runoff processes, snow hydrology, nutrient or contaminant export, ecohydrology or other catchment 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

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
- Methods accounting for concentrations of pathogens or contaminants at or below the limits of detection
- 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, pesticides and biocides, personal care products, organic pollutants and heavy metals, chlorinated compounds, PFAS) 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 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 to quantify diffuse and point source inputs
- Modelling approaches (including hydrology and sediment transport) to simulate pollutants transport and fate at several spatial and temporal scales
- Modelling tools for decision support and evaluation of mitigation measures, for example
- Methods to evaluate water quality modelling uncertainty, and/or combining data and modeling (data assimilation)
- 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:
• Plastic 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.

The application of multi-datasets and multi-objective functions has proven to improve the performance of hydrologic, ecological 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 or pollutant concentration) 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 helps to improve our understanding of the model functioning in relation to catchment processes. Finally, the quantification of multiple uncertainty sources enables the identification of their individual contributions that is critical for uncertainty reduction and environmental decision making.

In this respect, Bayesian approaches have become increasingly popular in hydrological, ecological and water quality modelling thanks to their ability to handle uncertainty comprehensively. This is particularly relevant for environmental decision making, where Bayesian inference enables the consideration of predictions reliability on decisions and relating uncertainties to a decision makers’ risk attitudes and preferences, all while accounting for the uncertainty related to our system understanding and random processes. Graphical Bayesian Belief Networks and related approaches (hierarchical models, ‘hybrid’ mechanistic/data-driven models) are increasingly being used as powerful decision support tools, facilitating stakeholder engagement in the model building process and allowing for adaptive management within an uncertainty framework.

This session gathers contributions that apply one or more of the multi-aspects in hydrological, ecological and water quality studies using diverse methodological approaches. It also aims to review advances and applications in the field of Bayesian water quality modelling and compare the capabilities of different software and procedural choices to consolidate and set new directions, with a specific emphasis on the utility of Bayesian water quality models in supporting decision making.

Long-term climate change, extreme events, and seasonal variations in weather have profound impacts on water quality of rivers, lakes, and reservoirs. This implies a pressing need for tools anticipating the impacts of these environmental changes, and enabling effective water management that safeguards the ecosystem goods and services freshwaters provide. Scientific studies typically omit the impacts of climate on water quality. To tackle this gap, this session looks for research results related to the impact of climate change on water quality. We welcome climate attribution results, studies using data-driven and remote sensing techniques and model projects of climate change from local to global scales. We are also interested in water quality studies within the regional and global water sectors Inter-Sectoral Impact Model Intercomparison Program (ISIMIP).

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.

Catchments are immensely complex 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. To place hydrology on a solid theoretical footing, the multitude of responses, interactions and feedbacks developing in the critical zone need to be disentangled and understood, and robust hydrological regularities need to be sought. This will improve our ability to make hydrological predictions under different and continuously changing climatic conditions and in places in which we do not have measurements.

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. Understanding and quantifying the drivers of catchment similarity and how that may be used to transfer knowledge in space and time (regionalization);
4. Studies that use, extend, or re-assess known hydrological regularities (e.g. the Budyko hypothesis) for predictions under changing conditions;
5. Data-based analyses and modelling studies aiming to evaluate and/or improve hydrologic simulations under historic climatic variability and change;
6. Efforts to improve the realism of hydrological projections under future climate scenarios;
7. 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, riverine and anthropogenic processes, and their interactions. The natural oscillation between flood-rich and flood-poor periods superimposes with anthropogenic climate change and human interventions 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 occurrence. 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 welcome as well. 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 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 spatial rainfall and catchment conditions shaping flood patterns
- Detection and attribution of flood hazard changes, such as atmospheric drivers, land use controls, natural water retention measures, 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.

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. Studies that investigate both types of extremes are of particular interest. Submissions from early-career researchers are especially encouraged.

With global climate change the frequency and intensity of floods and droughts are increasing in many parts of the world. Floods and droughts cover the entire hydrological spectrum with many similarities and links between the two types of extremes. Approaches, tools and management strategies can be, in some way, applicable to both contradicting extremes. For example, stress testing and storyline approaches have been developed recently to better understand systems under extreme conditions. They explicitly seek to understand the drivers of hydro-climatological extremes and their management implications. Stress tests and storylines can be informed by expert knowledge and used in conjunction with traditional sources of information (such as climate model projections). From a management perspective, coupling of flood risk reduction with drought management is one key to sustainable future water management.
We welcome contributions focusing on the whole strategic and operative management processes of these extreme events. We welcome contributions on the following topics:
- Stress testing approaches to analyse hydrological or climatological extremes
- Modelling experiments for the hydrological hazards, sensitivity and their consequences
- Interdisciplinary approaches for managing scarce water resources and flooding event and to support decision-making (e.g. public water supply, agriculture, industry or environmental water use)
- Stress tests to complement climate change scenarios to identify system vulnerability, hazard risk, tipping points and low-likelihood, high impact events

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 hydrological forecasting, 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) 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 modeling;

(iv) synthesis studies 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.

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.

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

Hydroinformatics has emerged over the last decades to become a recognised and established field of independent research within the hydrological sciences. Hydroinformatics is concerned with the development and hydrological application of mathematical modelling, information technology, systems science and computational intelligence tools. We also have to face the challenges of Big Data: large data sets, both in size and complexity. Methods and technologies for data handling, visualization and knowledge acquisition are more and more often referred to as Data Science.

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:

* Predictive and analytical 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 the analysis of complex data sets, including remote sensing data: principal and independent component analysis, time series analysis, information 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
* Software architectures for linking 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.

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. Abstracts are solicited 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) Integrating deep learning with process-based models and/or physical understanding.
(3) Improving understanding of the (internal) states/representations of deep learning models.
(4) Understanding the reliability of deep learning, e.g., under non-stationarity.
(5) Deriving scaling relationships or process-related insights with deep learning.
(6) Modeling human behavior and impacts on the hydrological cycle.
(7) Extreme event analysis, detection, and mitigation.
(8) Natural Language Processing in support of models and/or modeling workflows.