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.

The ever-increasing amount of data available in the water, earth and environmental sciences requires new approaches and more advanced methods that can quantify and measure the relationships in these data sets but also their uncertainty. Remote sensing, improved and cheaper measurement technology and global databases have steadily improved our information on processes, but require an understanding of the interplay of these data and their dependence.
Clustering and classification algorithms are increasingly and extensively applied in hydrology as the need for pattern recognition and data mining tasks persists with higher availability of large multivariate datasets. While both approaches share the goal of dividing data into convenient groups, classification approaches pre-define such groups (i.e. supervised learning) whereas clustering approaches group data with similar properties without preconceived notions about which groups are expected to be in the data (i.e. unsupervised learning).
Geostatistical methods are commonly applied in the water, earth and environmental sciences to quantify spatial variation, produce interpolated maps with quantified uncertainty and optimize spatial sampling designs. Space-time geostatistics explores the dynamic aspects of environmental processes and characterise the dynamic variation in terms of correlations. Geostatistics can also be combined with machine learning and mechanistic models to improve the modelling of real-world processes and patterns. Such methods are used to model soil properties, produce climate model outputs, simulate hydrological processes, and to better understand and predict uncertainties overall.
Topics covered in this session are:
1) How can clustering/classification approaches increase our understanding and improve our prediction of hydrological processes?
2) To what extent should clustering/classification algorithm settings be finetuned for hydrological applications?
3) How can geostatistical approaches be used for the characterization of uncertainties and error propagation?
4) How can spatial and temporal aspects be combined in geostatistics and how do they improve our understanding of hydrological processes?
5) What is the benefit of integrating machine-learning approaches to geostatistics?

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

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

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

Understanding and further predicting the incidence and severity of hydrometeorological hazards, such as floods, droughts, land slides and storm surges, are a key measure for risk mitigation, building resilience and supporting sustainable socio-economic development. This has become more important when our societies are facing climate change alongside the pressures induced by population growth, urbanisation and land use change. While traditionally physically based modelling approaches remain as a major tool base for studying the prognostics and diagnostics of these hazards, the ever high level of complexity of the underlying process and the interaction between the nature and human interface, and more importantly, the increasingly availability of new observations datasets, have necessitated many applications of tools and methods in the domain of hydroinformatics, such as data-driven modelling, machine learning, data fusion, alongside conventional sptial-temporal statistical analysis tools.

The aim of this session is to provide a platform and an opportunity to demonstrate and discuss innovative and recent advances of hydroinformatics applications and methodologies for analysing and producing diagnostics and prognostics of hydrometeorological hazards. It also aims to provide a forum for researchers from a variety of fields to effectively communicate their research. Submissions related to the following non-exhaustive topics are particularly welcome.
1. Spatial and temporal analysis of the incidence and distribution of hydrometeorological hazards;
2. Machine learning (e.g., CNN, GNN) in analysing and predicting hydrometeorological hazards.
3. Uncertainty quantification of coupled models, such as atmospheric-hydrological/hydrodynamic in the applications of diagnosing and predicting hydrometeorological hazards;
4. Development in quantitative methods for analysing compound hydrometeorological hazards;
5. Data assimilation and fusion of heterogeneous observations in hazards modelling, e.g., satellite-borne sensors and rainfall radars;
6. HPC (GPU) based algorithms and practice dealing with very large size datasets in prognostic modelling of hydrometeorological hazards, e.g., climate projections.
7. Modelling interface with human interactions in decision making, mitigation and impact studies.

Flash floods triggered by heavy precipitation in small- to medium-sized catchments often cause catastrophic damages, which are largely explained by the very short response times and high unit peak discharge. Often, they are also associated with geomorphic processes such as erosion, sediment transport, debris flows and shallow landslides. The anticipation of such events is crucial for efficient crisis management. However, their predictability is still affected by large uncertainties, due to the fast evolution of triggering rainfall events, the lack of appropriate observations, the changes due to a warming climate, the high variability and non-linearity in the physical processes, the high variability of societal exposure, and the complexity of societal vulnerability.
This session aims to illustrate current advances in monitoring, modeling, and short-range forecasting of flash floods and associated geomorphic processes, including their societal impacts.
Contributions related to recent and significant floods are particularly encouraged.
This session aims to specifically cover the following scientific themes:
- Monitoring and nowcasting of heavy precipitation events based on radar and remote-sensing systems (satellite, lightning, ..), to complement rain gauge networks
- Short-range (0-6h) heavy precipitation forecasting based on NWP models and/or ML-based approaches, with a focus on seamless forecasting strategies, and ensemble or probabilistic strategies for the representation of uncertainties.
- Understanding and modeling of flash floods, rainfall-induced hydro-geomorphic processes and their cascading effects, at appropriate space-time scales.
- Development of integrated hydro-meteorological forecasting chains and new modeling approaches for predicting flash floods and/or rainfall-induced geomorphic hazards in gauged and ungauged basins.
- New direct and indirect (proxy data) observation techniques and strategies for the observation or monitoring of hydrological reactions and geomorphic processes, and the validation of forecasting approaches.
- Development of impact-based modeling and forecasting approaches, including inundation mapping and/or specific impacts modeling approaches for the representation of societal vulnerability.

Drought and water scarcity affect many regions of the Earth, including areas generally considered water rich. A prime example is the severe 2022 European drought, caused by a widespread and persistent lack of precipitation combined with a sequence of heatwaves from May onwards. The projected increase in the severity and frequency of droughts may lead to an increase of water scarcity, particularly in regions that are already water-stressed, and where overexploitation of available water resources can exacerbate the consequences droughts have. In the worst case, this can lead to long-term environmental and socio-economic impacts. Drought Monitoring and Forecasting are recognized as one of three pillars of effective drought management, and it is, therefore, necessary to improve both monitoring and sub-seasonal to seasonal forecasting for droughts and water availability, and to develop innovative indicators and methodologies that translate the data and information to underpin effective drought early warning and risk management.

This session addresses statistical, remote sensing and physically-based techniques, aimed at monitoring, modelling and forecasting hydro-meteorological variables relevant to drought and water scarcity. These include, but are not limited to: precipitation, snow cover, soil moisture, streamflow, groundwater levels, and extreme temperatures. The development and implementation of drought indicators meaningful to decision-making processes, and ways of presenting and integrating these with the needs and knowledges of water managers, policymakers and other stakeholders, are further issues that are addressed. Contributions focusing on the interrelationship and feedbacks between drought and water scarcity, hydrological impacts, and society are also welcomed. The session aims to bring together scientists, practitioners and stakeholders in the fields of hydrology and meteorology, as well as in the fields of water resources and drought risk management. Particularly welcome are applications and real-world case studies, both from regions that have long been exposed to significant water stress, as well as regions that are increasingly experiencing water shortages due to drought and where drought warning, supported by state-of-the-art monitoring and forecasting of water resources availability, is likely to become more important in the future.

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

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

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

Contributions are welcome from both scientists and practitioners who are involved in developing and using operational forecasting and/or management systems for climate and water-related hazards, such as flood, drought, tsunami, landslide, hurricane, hydropower, pollution etc. We also welcome contributions from early career practitioners and scientists.

The Sendai Framework for Disaster Risk Reduction (SFDRR) and its seventh global target recognizes that increased efforts are required to develop risk-informed and impact-based multi-hazard early warning systems. Despite significant advances in disaster forecasting and warning technology, it remains challenging to produce useful forecasts and warnings that are understood and used to trigger early actions. Overcoming these challenges requires understanding of the reliability of forecast tools and implementation barriers in combination with the development of new risk-informed processes. It also requires a commitment to create and share risk and impact data and to co-produce impact-based forecasting models and services. To deal with the problem of coming into action in response to imperfect forecasts, novel science-based concepts have recently emerged. As an example, Forecast-based Financing and Impact-based Multi-Hazard Early Warning Systems are currently being implemented operationally by both governmental and non-governmental organisations in several countries as a result of increasing international effort by several organizations such as the WMO, World Bank, IFRC and UNDRR to reduce disaster losses and ensuring reaching the objectives of SFDRR. This session aims to showcase lessons learnt and best practices on impact-based multi-hazards early warning system from the perspective of both the knowledge producers and users. It presents novel methods to translate forecast of various climate-related and geohazards into an impact-based forecast. The session addresses the role of humanitarian agencies, scientists and communities at risk in creating standard operating procedures for economically feasible actions and reflects on the influence of forecast uncertainty across different time scales in decision-making. Moreover, it provides an overview of state-of-the-art methods, such as using Artificial Intelligence, big data and space applications, and presents innovative ways of addressing the difficulties in implementing forecast-based actions. We invite submissions on the development and use of operational impact-based forecast systems for early action; developing cost-efficient portfolios of early actions for climate/geo-related impact preparedness such as cash-transfer for droughts, weather-based insurance for floods; assessments on the types and costs of possible forecast-based disaster risk management actions; practical applications of impact forecasts.

Many water sectors are already having to cope with extreme weather events, climate variability and change. In this context, predictions on sub-seasonal and seasonal to decadal timescales (i.e. horizons ranging from months to a decade) are an essential part of hydrological forecasting. By providing science-based and user-specific information on potential impacts of variations in water availability, operational hydro-meteorological and climate services are invaluable to a range of water sectors such as water resources management, drinking water supply, transport, energy production, agriculture, disaster risk reduction, forestry, health, insurance, tourism and infrastructure.

This session aims to cover the research and operational advances in science as well as applied climate and hydro-meteorological forecasting, and their implications on predicting water availability and demand for servicing water sectors. It welcomes, without being restricted to, presentations on:
- Technical challenges in making use of forecast or projected climate data for hydrological modelling (e.g. downscaling, bias correction, temporal disaggregation, spatial interpolation),
- Lessons learnt from forecasting and managing present day extreme conditions,
- Improved representations of hydrological extremes in a future climate,
- Seamless forecasting, including downscaling and statistical post- and pre-processing,
- Propagation of uncertainty through the forecasting chain for impact assessment and decision-making,
- Operational hydro-meteorological forecasting systems, hydro-climate services, and tools,
- Effective methods to link stakeholder interests and scientific expertise (e.g. service co-generation).

The session will bring together research scientists and operational managers in the fields of hydrology, water use, meteorology and climate, with the aim of sharing experiences and initiating discussions on this momentous topic. We encourage presentations that utilise the WWRP/WCRP subseasonal-to-seasonal (S2S) prediction project database, hydrological relevant applications, and S2S forecasting and predictions within the Water-Food-Energy Nexus.

The occurrences of extreme flood events have increased globally in the last two decades as noted by recent rare and catastrophic flooding events in Germany, Belgium, China, the USA and India during the monsoon season. Advanced innovative methods and conceptual improvements in existing approaches are required to address the modelling and management of the spatial and temporal complexity of extreme floods. The observed increase in frequency and severity of events can be predicted by joint probabilistic analyses of precipitation and river flow extremes. Evidence from the rare extreme events indicates that assumptions of Holocene climate stationarity is not applicable anymore for hydrologic analysis and design. Prediction of region-scale and localized extreme events well ahead of time is a real challenge. New design protocols have required that account for uncertainties in future meteorological events and provide flexibility in the design and operation of infrastructure to minimize the consequences of extreme events. Understanding the mechanisms of extreme precipitation and its hydro meteorological connection with flooding, especially under the circumstances of global climate change, is critical for flood prevention and mitigation. This session invites research papers that focus on scientific and technological developments in extreme precipitation estimation, flood monitoring, and flood modelling, or ensemble flood modelling with the end goal of improving flood prevention and mitigation. The research studies discussing advancements in situ measurement and remote sensing of extreme precipitation, advances in rainfall-runoff modelling in the data scarce region, statistical and hydrological analysis of extreme precipitation and flood, analysis of numerical weather predictions (NWPs) of hydrometeorological forecasts, flood forecasting and warning, and impact assessment of climate change and land use/cover change on flood are also invited. Research works that emphasize and discuss case studies on modelling extreme events are also expected to gain and learn from insights gained from flood disaster modelling and management. Studies involving hydrologic and hydraulic modelling in data scarce regions will also be welcome in this session. The session also encourages the studies and discussion of the advantages of probabilistic approach of the ensemble flood forecasting over the traditional deterministic approach of flood forecasting.

To alleviate the adverse effects of urban floods, non-structural approaches especially early flood warning systems have attracted more attention in recent decades due mainly to the time saving for development and operation, cost-effectiveness and no extra space or facilities required for new construction or physical modification. Development of real-time urban flood forecasting (RTUFF) systems has been more popular in the early flood warning systems. However, unique features of urban floods can be used to determine the requirements for spatial and temporal data, types of flood modelling, the inclusion of potential flood impacts and key performance indicators.
The data used for RTUFF can be taken from various sources to which the access is sometimes limited or challenging. In addition, RTUFF typically requires modelling of distributed systems with high spatial and temporal complexity, which is overstressed by spatial limitation as well as short preparation time. These restrictions may hinder developing RTUFF modelling, assessing their performance and applications. A significant breakthrough has been made over the recent decades to overcome some major challenges in main steps of RTUFF as "data collection and preparation", "model development", "performance assessment" and "applications".

This session aims to address the challenges and advances through state-of-the-art techniques and new developments and frameworks, equipment, software tools and hardware facilities, integration of existing methods and modelling to contemporary algorithms, digital innovations and applications to new pilot studies.

This session will focus on new advances, modelling and applications of RTUFF related to- but not limited- the following research areas:
• Hydrological data collection, analysis, imputation, assimilation and fusion taken from various data sources including ground stations, radar stations, remote sensing (aerial/satellite)
• RTUFF modelling including physically/processed-based, conceptually-based, experimentally-based or data-driven modelling such as artificial Intelligence (AI), machine learning (ML)
• Application RTUFF for flood alleviation or engagement with the public and authorities, such as early warning and early action systems, digital innovations such as digital twins (DT), or integrated with digital technologies such as augmented reality (AR) and virtual reality (VR).

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

Under the projected climate conditions for many regions of the world, precipitation variability and the occurrence and severity of drought are likely to increase. Consequently, improved planning and strategies for recovering, distributing, and utilizing water resources required for domestic and public water use, power generation, and agriculture will be crucial for ameliorating socioeconomic costs incurred during periods of water scarcity while maintaining environmental flow requirements. Because irrigation accounts for 70% of global freshwater withdrawals, future allocations of water resources to water providers and users within this sector will necessitate improvements in conveyance efficiencies and crop water productivities with involvement of irrigators and growers. As water demand and scarcity increases, the rational and sustainable management of water for food and energy will require involvement of all stakeholders to balance the needs of people, the environment, and the economy. Planning and responding appropriately to water use restrictions and precipitation shortfalls under drought within the agricultural sector will be crucial for lessening the detrimental societal impacts and ameliorating risk for all water users. This session invites contributions that present strategies, tools, and technologies that have the potential to improve crop water productivity, reduce water waste in agriculture, and optimize allocation of water resources among users under water scarce conditions. Specific topics may include:
• Use of remotely and proximally sensed data and hydrological models to manage irrigation and improve water productivity and increase water savings in crop production.
• Evaluation of frameworks and implementation of water distribution strategies and models in municipalities, watersheds, and water districts.
• Hydrological-climate linked processes in semi-arid regions and associated periods of water scarcity and drought indicators necessary for planning water allocations.
• Use of reclaimed water and waste streams and other innovative water management strategies
• Analysis of trends in surface and groundwater availability and quality and associated environmental effects caused by utilization and management.
• Analysis of policies that support improved water productivity in agriculture and that ensure equitable distribution of water resources among sectors.

Water sustains societies, economies and ecosystem services globally. Increasing water demands driven by ongoing socioeconomic development, coupled with shifts in water availability due to climate change and variability and land use change, are increasing competition and conflict over access to and use of freshwater resources in many regions around the world. To address these challenges, integrative approaches to water management and policy are required to balance and manage trade-offs between social, economic and environmental uses of water. In addition, there is an emerging need for adaptive and flexible solutions capable of updating decisions to newly available information, often issued in the form of weather or streamflow forecasts or extracted from observational data collected via pervasive sensor networks, remote sensing, cyberinfrastructure, or crowdsourcing. This session will provide a forum for showcasing novel and emerging research at the intersection of agricultural production, energy security, water supply, economic development, and environmental conservation. In particular, we encourage contributions to the session that: (i) identify knowledge gaps and improvements to understanding about the critical interconnections, feedbacks, and risks between system components, (ii) highlight development of new methods or tools for evaluating and monitoring trade-offs and performance in water allocation and management between different users and sectors, (iii) evaluate alternative technological, policy, and/or governance interventions to address water-food-energy-environment system challenges in different locations and at various scales (local, regional, and/or global), and (iv) advance the use of multi-sectoral forecasts combined with data analytics machine learning algorithms for informing the real-time control of water systems. We welcome real-world examples on the successful application of these methods to facilitate integrated planning and management of water-food-energy-environment systems.

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

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

Questions of interest include:
- Prediction of water availability and storage capabilities for hydropower production
- Prediction and quantification of the space-time dependences and the positive/negative feedbacks between wind/solar energies, water cycle and hydropower
- Energy, land use and water supply interactions during transitions
- Policy requirements or climate strategies needed to manage and mitigate risks in the transition
- Energy production impacts on ecosystems such as hydropeaking effects on natural flow regimes.

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

The Water, Energy, Food, and Environment (WEFE) components of the Nexus are in rapid transition, driven by forces such as socioeconomic, demographic, climatic, and technological changes as well as policies intended to meet Sustainable Development Goals (SDGs) and other societal priorities. These dynamics weave across spatial scales, connecting global markets and trends to regional and sub-regional economies. At the same time, resources are often locally managed under varying administrative jurisdictions closely tied to inherent characteristics of each commodity such as river basins for water, grid regions for electricity and land-use boundaries for agriculture. Local decisions, in turn, are critical in deciding the success and consequences of national and global policies, as well as their impact. Thus, there is a growing need to better characterise the Nexus to guide robust and consistent multi-scale decision-making under a changing climate. One of the hardest challenges in science is turning research into practice, having a concrete impact on policies and operations, and engaging stakeholders in a way that they truly adopt the proposed solutions.

This session aims to address these challenges at different scales (local to regional) in nascent infrastructure planning and sectoral transitions, with a large focus on solutions generated by European research projects and other international experiences. Contributions can include work dealing with applications of existing nexus approaches in sustainability assessment, climate-resilient and adaptive nexus management, and design of future developments, as well as new methods and nature-based solutions that address existing gaps related to incorporating processes at different scales, bridging data gaps, improving optimisation approaches, or dealing with transboundary issues and Nexus governance. Success cases of impactful research on local, national, and/or international policies and decisions are also welcome.

Land use and land cover (LULC) changes are one of the main drivers of change to hydrological processes, altering the ecosystem dynamics and impacting the production of water-related ecosystem services (WES) with different levels of societal impact. These LULC changes can emerge directly from anthropogenic interventions, or indirectly as the result of climate change. There is an extensive body of research investigating the impact of LULC changes on streamflow dynamics, but less so on other elements of the hydrological cycle (e.g. groundwater quantity and quality, evaporation and transpiration, soil moisture and rainfall interception) and associated ecosystem services. Changes to these elements can possibly lead to non-local and non-linear effects on ecosystem services, which need to be understood to inform effective and equitable water resource management.

This session welcomes studies that address the impacts of LULC changes on all water resources and hydrological processes, and associated WES, such as flood regulation, moisture recycling, temperature regulation, and food provisioning. Furthermore, beyond impact assessments, we welcome scholars that address policy options to mitigate harmful impacts on WES. More specifically, we welcome studies including, but not limited to:

• Advances in the quantification of hydrological impacts of LULC changes through modelling and experimental data, including water quantity and quality
• Disentanglement of LULC change impacts on all water resources (blue surface and groundwater, green water, atmospheric water) and associated WES
• Analysis and evaluation of policy interventions to mitigate impacts, such as ecological restoration schemes and nature-based solutions, with respect to their effectiveness and feasibility to protect and/or restore WES
• Advances in (interdisciplinary) methodologies for identifying WES, as well as studies highlighting spatial assessments of WES

The field of socio-hydrology and hydro-social research emerged as an attempt to better understand the dynamic interactions and feedbacks within diverse coupled human-water systems and its implications for the assessment and management of water resources and associated risks.
An integrated perspective offers novel entry points for a more fertile engagement between hydrological and social sciences across different scales ranging from the plot level to entire watersheds. Its interdisciplinary nature encompasses (and integrates) various methodological approaches, epistemologies, and disciplines.
We welcome contributions from researchers from social and natural sciences who are keen to look beyond their research perspective and who like to discuss their research findings in a broader context of coupled human water systems. Papers should 1) contribute to the understanding of complex human-water interactions and their management, 2) discuss the benefits and shortcomings of different inter- and disciplinary perspectives based on empirical, conceptual or model-based research; and 3) shed light on the added value of socio-hydrological modelling and hydro-social analysis for water resources management, risk management and adaptation design.

Water utilities and municipalities must embrace technological innovation to address the exacerbating challenges and uncertainties posed by climate change, urbanization, and population growth. The progressive transformation of urban water infrastructure and the adoption of digital solutions for water resources are opening new opportunities for the design, planning, and management of more sustainable and resilient urban water networks and human-water systems across urban scales. The “digital water” revolution is strengthening at the same time the interconnection between urban water systems (e.g., drinking water, wastewater, urban drainage) and other critical infrastructures (e.g., energy grids, transportation networks). This interconnection motivates the development of novel approaches accounting for the intrinsic complexity of such coupled systems.
This session aims to provide an active forum to discuss and exchange knowledge on state-of-the-art and emerging tools, frameworks, and methodologies for planning and management of modern urban water infrastructure, with a particular focus on digitalization and/or interconnections with other systems. Topics and applications could belong to any area of urban water network analysis, modelling and management, including, e.g., intelligent sensors and advanced metering, digital twins, asset management, decision making, novel applications of IoT, and challenges to their implementation or risk of lock-in of rigid system designs. Additional topics may include big-data analytics and information retrieval, data-driven behavioural analysis, artificial intelligence for water applications, descriptive and predictive models of, e.g., water demand, sewer system flow or flood extend, experimental approaches to demand management, water demand and supply optimization, real-time control of urban drainage systems, or the identification of trends and anomalies in hydraulic sensor data (e.g., for leak detection or prior to model calibration). Interesting investigations on interconnected systems can include, for example, cyber-physical security of urban water systems (i.e., communication infrastructure), combined reliability and assessment studies on urban metabolism, or minimization of flood impacts on urban networks.

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

This session aims to provide researchers with a platform to present and discuss the application, knowledge gaps and future research directions of urban GI and how sustainable green solutions can contribute towards an integrated and sustainable urban hazard management approach. We welcome original research contributions across a series of disciplines with a hydrological, climatic, soil sciences, ecological and geomorphological focus, and encourage the submission of abstracts which demonstrate the use of GI at a wide range of scales and geographical distributions. We invite contributions focusing on (but not restricted to):

· Monitored case studies of GI, Sustainable Drainage Systems (SuDS) or Nature Based Solutions (NBS), which provide an evidence base for integration within a wider hazard management system;

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

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

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

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

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

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

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

Groundwater provides about 40% of all human water abstractions and is an essential water source for freshwater biota in rivers, lakes, and wetlands. Groundwater is, therefore, essential to ensuring sustainable water availability and a critical part of reaching sustainable development goal 6 (SDG6): “Ensuring availability and sustainable management of water and sanitation for all”.
The development of groundwater models and the analysis of groundwater data from national monitoring networks to global datasets have helped to push the boundaries of our understanding of groundwater processes. In particular, knowledge of the exchange between surface and subsurface waters is essential for determining the water balance at larger scales. Surface and subsurface water exchanges and inter-catchment groundwater flow affect water, pollutant, and nutrient fluxes, bio-organisms in streams, and the groundwater itself. Additionally, human activities (e.g., pumping/irrigation) increasingly affect groundwater flow processes and the exchange between surface and subsurface waters.
In this session, we focus on how groundwater monitoring, data analysis and modelling is critical for achieving sustainable water management. In particular, we highlight the increasing interest in the large-scale study of groundwater availability, quality, and processes (including groundwater recharge) and discuss current obstacles related to data availability and model design. We also focus on the implications of such research in informing effective policy in groundwater management.
Therefore, we seek contributions that address issues including:
• Regional to global groundwater-related datasets and big-data assessments
• Transboundary and inter-catchment assessments of groundwater processes
• Identification of dominant controls on groundwater processes across large domains
• Surface-subsurface water exchange at catchment to global scales and its effects on hydrological extremes (drought/flood), water availability, and solute/pollutant transport
• Effects of climate change, land use change, and change in water demand on large-scale groundwater
• Implications of groundwater monitoring and modelling, integrated water management, and global water policies
• Policy considerations in groundwater management ensuring adequate access to water resources
Solicited authors:
Nils Moosdorf

We invite presentations concerning soil moisture estimation, including remote sensing, field experiments, land surface modelling and data assimilation and the establishment of fiducial reference measurements (FRMs). The technique of microwave remote sensing has made much progress toward its high potential to retrieve surface soil moisture at different scales. From local to landscape scales, several field or aircraft experiments (e.g. SMAPvex) have been organised to improve our understanding of active and passive microwave soil moisture sensing, including the effects of soil roughness, vegetation, spatial heterogeneities, and topography. At continental scales, a series of several passive and active microwave space sensors, including SMMR (1978-1987), AMSR (2002-), ERS/SCAT (1992-2000) provided information on surface soil moisture. Current investigations in L-band passive microwave with SMOS (2009-) and SMAP (2015-), and in active microwave with Metop/Ascat series (2006-) and Sentinel-1, enable accurate quantification of the soil moisture at regional and global scales. Future missions, such as the CIMR Copernicus High Priority Candidate Mission, the EPS-SG Metop-SG/SCA and continuity of the Sentinel programme, will further enhance soil moisture remote sensing accuracy and spatial resolution, and they will ensure continuity of multi-scale soil moisture measurements on climate scales.

We encourage submissions related to soil moisture remote sensing, including:
- Field experiment, theoretical advances in microwave modelling and calibration/validation activities.
- High spatial resolution soil moisture estimation based on e.g. Sentinel observations, GNSS reflections, or using novel downscaling methods.
- Preparation of future missions including CIMR, Metop-SG/SCA, SMOS-High Resolution, Terrestrial Water Resources Satellite, etc.
- Root zone soil moisture retrieval and soil moisture data assimilation in land surface models, hydrological models and in Numerical Weather Prediction models.
- Evaluation and trend analysis of soil moisture climate data records such as the ESA CCI soil moisture product as well as soil moisture from re-analysis.
- Inter-comparison and inter-validation between land surface models, remote sensing approaches and in-situ validation networks.
- Uncertainty characterization across scales.
- Soil moisture reference networks.
- Application of satellite soil moisture products for improving hydrological applications.

The socio-economic impacts associated with floods are increasing. Floods represent the most frequent and most impacting, in terms of the number of people affected, among the weather-related disasters: nearly 0.8 billion people were affected by inundations in the last decade, while the overall economic damage is estimated to be more than $300 billion.
In this context, remote sensing represents a valuable source of data and observations that may alleviate the decline in field surveys and gauging stations, especially in remote areas and developing countries. The implementation of remotely-sensed variables (such as digital elevation model, river width, flood extent, water level, flow velocities, land cover, etc.) in hydraulic modelling promises to considerably improve our process understanding and prediction. During the last decades, an increasing amount of research has been undertaken to better exploit the potential of current and future satellite observations, from both government-funded and commercial missions, as well as many datasets from airborne sensors carried on airplanes and drones. In particular, in recent years, the scientific community has shown how remotely sensed variables have the potential to play a key role in the calibration and validation of hydraulic models, as well as provide a breakthrough in real-time flood monitoring applications. With the proliferation of open data and more Earth observation data than ever before, this progress is expected to increase.
We encourage presentations related to flood monitoring and mapping through remotely sensed data including: - Remote sensing data for flood hazard and risk mapping, including commercial satellite missions as well as airborne sensors (aircraft and drones);
- Remote sensing techniques to monitor flood dynamics;
- The use of remotely sensed data for the calibration, or validation, of hydrological or hydraulic models;
- Data assimilation of remotely sensed data into hydrological and hydraulic models;
- Improvement of river discretization and monitoring based on Earth observations;
- River flow estimation from remote sensing

This session focuses on measurements and estimations of water levels, water extent, water storage and water discharge of water bodies such as rivers, lakes, floodplains and wetlands, and groundwater, through combined use of remote sensing and in situ measurements. Contributions that also cover aspects of assimilation of remote sensing and in situ data within hydrodynamic models are welcome and encouraged.

The monitoring of river water level, river discharge, water bodies extent, storage in lakes and reservoirs, and floodplain dynamics plays a key role in assessing water resources, understanding surface water dynamics, characterising and mitigating water related risks and enabling integrated management of water resources and aquatic ecosystems.

While in situ measurement networks play a central role in the monitoring effort, remote sensing techniques contribute by providing near real time measurements and long homogeneous time series to study the impact of climate change, over various scales from local to regional and global.

During the past thirty years a large number of satellites and sensors has been developed and launched allowing to quantify and monitor the extent of open water bodies (passive and active microwave, optical), the water levels (radar and laser altimetry), the global water storage and its changes (variable gravity). River discharge, a key variable of hydrological dynamics, can be estimated by combining space/in situ observations and modelling, although still challenging with available spaceborne techniques. Interferometric Synthetic Aperture Radar (InSAR) is also commonly used to understand wetland connectivity, floodplain dynamics and surface water level changes, with more complex stacking processes to study the relationship between ground deformation and changes in groundwater resources.

Traditional instruments contribute to long-term water level monitoring and provide baseline databases. Scientific applications of more complex technologies like the SAR altimetry on CryoSat-2, Sentinel-3A/B and Sentinel-6 missions are maturing, including the Fully-Focused SAR technique offering very-high resolution. The future SWOT mission will open up many new hydrology-related opportunities. Preparation studies results for Sentinel-3 Next Generation and CRISTAL are encouraged.

Snow constitutes a freshwater resource for over a billion people world-wide. High percentage of this water resource mainly comes from seasonal snow located in mid-latitude regions. The current warming situation alerts that these snow water storages are in high risk to be dramatically reduced, affecting not only the water supply but also the ecosystem over these areas. Therefore, understanding seasonal snow dynamics, possible changes and implications have become crucial for water resources management. Remote sensing has proven to be the main technique used to monitor the snow properties across mid-large extensions and their hydrological implications, for decades now. Moreover, the recent advances, which are mainly focused on the study of snow properties at higher spatio-temporal scales (e.g., small-scale snow-topography interactions, snow-vegetation interaction, diurnal variation of snow, rain over snow events), are helping to understand better snow accumulation, distribution and ablation dynamics.
This session is focused on studies linking the use of remote sensing of seasonal snow in hydrological applications: techniques and data from different technologies, such as time-lapse imagery, laser scanners, radar, optical photography, thermal and hyperspectral technologies, or other new applications, with the aim of quantifying and better understanding snow characteristics (i.e. snow grain size, snow depth, albedo, pollution load, snow specific area and snow density), snow related processes (snowfall, melting, evaporation and sublimation), snow dynamics, snow modelling, snow hydrological impacts and snow environmental effects. Works covering different spatial scales, from the plot to the global, and temporal scales, from instantaneous to multiyear, are welcome.

Agriculture is the largest consumer of water worldwide and at the same time irrigation is a sector where huge differences between modern technology and traditional practices do exist. Furthermore, reliable and organized data about water withdrawals for agricultural purposes are generally lacking worldwide, thus making irrigation the missing variable to close the water budget over anthropized basins. As a result, building systems for improving water use efficiency in agriculture is not an easy task, even though it is an immediate requirement of human society for sustaining the global food security, rationally managing the resource and reducing causes of poverties, migrations and conflicts among states, which depend on trans-boundary river basins. Climate changes and increasing human pressure together with traditional wasteful irrigation practices are enhancing the conflictual problems in water use also in countries traditionally rich in water. Hence, saving irrigation water improving irrigation efficiency on large areas with modern techniques is an urgent action to do. In fact, it is well known that agriculture uses large volumes of water with low irrigation efficiency, accounting in Europe for around 24% of the total water use, with peak of 80% in the Southern Mediterranean part and may reach the same percentage in Mediterranean non-EU countries (EEA, 2009; Zucaro 2014). North Africa region has the lowest per-capita freshwater resource availability among all Regions of the world (FAO, 2018).
Several studies have recently explored the possibility of monitoring irrigation dynamics and by optimizing irrigation water management to achieve precision farming exploiting remote sensing information combined with ground data and/or water balance modelling.
In this session, we will focus on: the use of remote sensing data to estimate irrigation volumes and timing; management of irrigation using hydrological modeling combined with satellite data; improving irrigation water use efficiency based on remote sensing vegetation indices, hydrological modeling, satellite soil moisture or land surface temperature data; precision farming with high resolution satellite data or drones; farm and irrigation district irrigation management; improving the performance of irrigation schemes; estimates of irrigation water requirements from ground and satellite data; ICT tools for real-time irrigation management with remote sensing and ground data coupled with hydrological modelling.

Remote sensing products have a high potential to contribute to monitoring and modelling of water resources. Nevertheless, their use by water managers is still limited due to lack of quality, resolution, trust, accessibility, or experience.
In this session, we look for new developments that support the use of remote sensing data for water management applications from local to global scales. We are looking for research to increase the quality of remote sensing products, such as higher resolution mapping of land use and/or agricultural practices or improved assessments of river discharge, lake and reservoir volumes, groundwater resources and drought monitoring/modelling. We are interested in quality assessment of remote sensing products through uncertainty analysis or evaluations using alternative sources of data. We also welcome contributions using a combination of different techniques (physically based models or artificial intelligence techniques) or a combination of different sources of data (remote sensing and in situ). Finally, we wish to attract presentations on developments of user-friendly platforms providing smooth access to remote sensing data for water applications.
We are particularly interested in applications of remote sensing to estimate the human water interactions such as dam operations and/or irrigations.

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

With the proliferation and wide accessibility of remotely sensed information, data from missions such as Landsat, Sentinel, and MODIS are being increasingly used to develop a better understanding of hydrological processes on the earth’s surface. Acquiring this understanding is a crucial prerequisite to ameliorate resource management, optimise the development of infrastructure, and adjust land use practices to changing climate conditions and hazards such as floods and droughts. However, many analyses incorporate remote sensing data by default and without a thorough critical examination of their applicability and limitations. In-situ data, though often less readily available and more eclectic, provide a valuable layer of information to act as a benchmark against methods relying solely on remotely sensed data.
This session aims to highlight innovative approaches to harnessing a synthesis of remotely sensed and in-situ data to better understand processes related to hydrology at regional and local scales in a variety of environments. We welcome contributions that focus on combining remote sensing and in-situ information and critically engage with this intersection with relation to:
- Processes such as evapotranspiration, infiltration, (Monsoon) inundations
- Hydrological extremes such as floods and droughts
- Hydrological processes shaping agricultural systems
- Intersections with societal processes and synergies with socio-hydrological approaches
- Coping with a sparsity of in-situ data in poorly gauged and ungauged basins
- Developing novel methods of gathering in-situ benchmark data to combine with remotely sensed approaches
- Reviewing recent synthesised advances of RS applications in hydrology, in natural and anthropised ecosystems
- Application of remote sensing in hydrological modelling, particularly using remotely sensed water cycle components to facilitate multi-variable calibration and spatial evaluation of hydrological models.

Rainfall is a “collective” phenomenon emerging from numerous drops. Understanding the relation between the physics of individual drops and that of a population of drops remains an open challenge, both scientifically and at the level of practical implications. This remains true also for solid precipitation. Hence, it is much needed to better understand small scale spatio-temporal precipitation variability, which is a key driving force of the hydrological response, especially in highly heterogeneous areas (mountains, cities). This hydrological response at the catchment scale is the result of the interplay between the space-time variability of precipitation, the catchment geomorphological / pedological / ecological characteristics and antecedent hydrological conditions. Therefore, (1) accurate measurement and prediction of the spatial and temporal distribution of precipitation over a catchment and (2) the efficient and appropriate description of the catchment properties are important issues in hydrology.

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

The assessment of precipitation variability and uncertainty is crucial in a variety of applications, such as flood risk forecasting, water resource assessments, evaluation of the hydrological impacts of climate change, determination of design floods, and hydrological modelling in general. This session aims to gather contributions on research, advanced applications, and future needs in the understanding and modelling of precipitation variability, and its sources of uncertainty.

Contributions focusing on one or more of the following issues are particularly welcome:
- Novel studies aimed at the assessment and representation of different sources of uncertainty versus natural variability of precipitation.
- Methods to account for accuracy in precipitation time series due to, e.g., change and improvement of observation networks.
- Uncertainty and variability in spatially and temporally heterogeneous multi-source precipitation products.
- Estimation of precipitation variability and uncertainty at ungauged sites.
- Precipitation data assimilation.
- Process conceptualization and approaches to modelling of precipitation at different spatial and temporal scales, including model parameter identification and calibration, and sensitivity analyses to parameterization and scales of process representation.
- Modelling approaches based on ensemble simulations and methods for synthetic representation of precipitation variability and uncertainty.
- Scaling and scale invariance properties of precipitation fields in space and/or in time.
- Physically and statistically based approaches to downscale information from meteorological and climate models to spatial and temporal scales useful for hydrological modelling and applications.

Hydroclimatic conditions and availability of water resources in space and time constitute important factors for maintaining adequate food supply, the quality of the environment, and the welfare of citizens and inhabitants, in the context of a post-pandemic sustainable growth and economic development. This session is designed to explore the impacts of hydroclimatic variability, climate change, and temporal and spatial availability of water resources on different factors, such as food production, population health, environment quality, and local ecosystem welfare.
We particularly welcome submissions on the following topics:
• Complex inter-linkages between hydroclimatic conditions, food production, and population health, including: extreme weather events, surface and subsurface water resources, surface temperatures, and their impacts on food security, livelihoods, and water- and food-borne illnesses in urban and rural environments.
• Quantitative assessment of surface-water and groundwater resources, and their contribution to agricultural system and ecosystem statuses.
• Spatiotemporal modeling of the availability of water resources, flooding, droughts, and climate change, in the context of water quality and usage for food production, agricultural irrigation, and health impacts over a wide range of spatiotemporal scales.
• Smart infrastructure for water usage, reduction of water losses, irrigation, environmental and ecological health monitoring, such as development of advanced sensors, remote sensing, data collection, and associated modeling approaches.
• Modelling tools for organizing integrated solutions for water supply, precision agriculture, ecosystem health monitoring, and characterization of environmental conditions.
• Water re-allocation and treatment for agricultural, environmental, and health related purposes.
• Impact assessment of water-related natural disasters, and anthropogenic forcing (e.g. inappropriate agricultural practices, and land usage) on the natural environment (e.g. health impacts from water and air, fragmentation of habitats, etc.)

Water resources managers and scientists are facing several challenges when applying climate models for hydrological variables. Indeed, a gap exists between what is provided by climate scenarios and what is needed and useful for water resources managers. In order to reduce this gap and enhance the assessment of climate change impacts, we need to improve our understanding, knowledge and model representations of the interactions between climate drivers and hydrological processes at the regional scale. This is essential to outline forecasts and assess extreme events risk, where uncertainty, probabilistic approaches ad prediction scenarios should be properly defined.
This session particularly welcomes, but is not limited to, contributions on:
- Advanced techniques to simulate and predict hydrological processes and water resources, with emphasis on stochastic and hybrid methods.
- Advanced techniques to simulate and predict hydroclimatic extreme events including compound extreme events relevant to water resources management (e.g. heatwaves and droughts).
- Holistic approaches to generate future water resources scenarios integrating also anthropogenic and environmental perspectives.
- Hydroclimatic change attribution studies using probabilistic approaches and novel causality frameworks with uncertainty assessment.
- Evaluation of climate models performance at the regional scale using observational data
This session is sponsored by the International Association of Hydrological Sciences (IAHS) and the World Meteorological Organization – Commission for Hydrology (WMO CHy) and it is also related to the scientific decade 2013–2022 of IAHS, entitled “Panta Rhei - Everything Flows”.

Extreme hydro-meteorological events drive many hydrologic and geomorphic hazards, such as floods, landslides and debris flows, which pose a significant threat to modern societies on a global scale. The continuous increase of population and urban settlements in hazard-prone areas in combination with evidence of changes in extreme weather events lead to a continuous increase in the risk associated with weather-induced hazards. To improve resilience and to design more effective mitigation strategies, we need to better understand the triggers of these hazards and the related aspects of vulnerability, risk, and mitigation.
This session aims at gathering contributions dealing with various hydro-meteorological hazards that address the aspects of vulnerability analysis, risk estimation, impact assessment, mitigation policies and communication strategies. Specifically, we aim to collect contributions from academia, the industry (e.g. insurance) and government agencies (e.g. civil protection) that will help identify the latest developments and ways forward for increasing the resilience of communities at local, regional and national scales, and proposals for improving the interaction between different entities and sciences.
Contributions focusing on, but not limited to, novel developments and findings on the following topics are particularly encouraged:
- Physical and social vulnerability analysis and impact assessment of hydro-meteorological hazards
- Advances in the estimation of socioeconomic risk from hydro-meteorological hazards
- Characteristics of weather and precipitation patterns leading to high-impact events
- Relationship between weather and precipitation patterns and socio-economic impacts
- Hazard mitigation procedures
- Strategies for increasing public awareness, preparedness, and self-protective response
- Impact-based forecast, warning systems, and rapid damage assessment.
- Insurance and reinsurance applications
This session is linked to an active special issue in Natural Hazards and Earth System Sciences (NHESS): https://nhess.copernicus.org/articles/special_issue1203.html

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

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

Over the last decades, a significant body of empirical and theoretical work has revealed the departure of statistical properties of hydrometeorological processes from the classical statistical prototype, as well as the scaling behaviour of their variables in general, and extremes in particular, in either state, space and/or time. Extremes and more generally the statistics of hydrometeorologic processes are the key input for hydrological applications, e.g. in natural catastrophe modelling. An example of this is the estimation of design rainfall. Beside the estimation of the absolute rainfall amount related to a certain return period, the intra-event rainfall distribution, its spatial extension and the rainfall intensities at neighbouring stations can be required depending on the intended application and thus the spatial and temporal scales of interest should be determined. Another good example are the large scale connections between hydrometeorologic extremes and climatic oscillations such as NAO or ENSO, and how these correlations can evolve in a changing climate. These are only two examples among numerous hydrologic applications.
On the one hand, the estimation of the hydrometeorological extremes and their probability distribution, the identification and incorporation of supporting information to improve these estimates, and their hydrologic application over a wide range of scales remain open challenges. On the other hand, hydrometeorologists had never access to so much computer power and data, including novel AI approaches, to face these open challenges.
This session welcomes, but is not limited to submissions on the following topics:
- Coupling stochastic approaches with deterministic hydrometeorological predictions, in order to better represent predictive uncertainty
- Development of robust statistics under non-stationary conditions for design purposes
- Development of parsimonious representations of probability distributions of hydrometeorological extremes over a wide range of spatial and temporal scales in risk analysis and hazard prediction
- Improvements for reliable estimation of extremes with high return periods under consideration of upper or lower limits due to physical constraints
- Linking underlying physics and hydroclimatic indices with stochastics of hydrometeorologic extremes
- Exploration of supporting data sets for additional stochastic information as well as the use of novel AI and machine learning approaches

Hydro-meteorological extremes such as floods, droughts, storms, or heatwaves often affect large regions therefore causing large damages and costs. Hazard and risk assessments, aiming at reducing the negative consequences of such extreme events, are often performed with a focus on one location despite the spatially compounding nature of extreme events. While spatial extremes receive a lot of attention by the media, little is known about their driving factors and it remains challenging to assess their risk by modelling approaches. Key challenges in advancing our understanding of spatial extremes and in developing new modeling approaches include the definition of multivariate events, the quantification of spatial dependence, the dealing with large dimensions, the introduction of flexible dependence structures, the estimation occurrence probabilities, the identification of potential drivers for spatial dependence, and linking different spatial scales. This session invites contributions which help to better understand processes governing spatial extremes and/or propose new ways of describing and modeling spatially compounding events at different spatial scales.

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

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

Typically, studies in this session are applied studies using fundamental characteristics of the atmospheric branch of the hydrologic cycle on different scales. These fundamentals include, but are not limited to, atmospheric circulation, humidity, hydroclimate frameworks, residence times, recycling ratios, sources and sinks of atmospheric moisture, energy balance and climatic extremes. Studies may also evaluate different sources of data for atmospheric hydrology and implications for inter-comparison and meta-analysis. For example, observations networks, isotopic studies, conceptual models, Budyko-based hydro climatological assessments, back-trajectories, reanalysis and fully coupled earth system model simulations.

A persistent rise in the mean global temperatures is observed due to the continuous accumulation of greenhouse gases within the atmospheric system. Global warming has resulted in climate change, manifesting changes in the hydrological cycle through long-term changes in temperature and precipitation patterns at different spatial and temporal scales. Thus, investigating trends and variability in climate extremes would help us quantify the regional climate change impacts. Moreover, stationarity assessment is essential for hydrologic design, particularly in a changing climate. In addition, the climate variability influences through large-scale oceanic-atmospheric circulations modulate the hydroclimatic means and extremes. Thus, it is inevitable to statistically analyze the long-term changes in hydroclimatic variables and explore their linkages to climate change and variability.

This session focuses on the application of statistical techniques for objectively assessing trends in hydroclimatic variables at different temporal, regional, and continental scales to assess any discernible links to climate variability and change. In addition, this session aims to explore the applicability of emerging techniques and approaches for detecting stationarity in hydroclimatic time series. This session will also invite submissions that develop and apply new indices for understanding regional hydroclimatological variability to aid water resources management. Research studies unravelling the climate variability effects on the hydroclimatic conditions at local and global scales will be appreciated. Further, research studies assessing the co-evolution of hydroclimatic variables under the influence of climate variability and change will also be welcomed.

The conservation and restoration of aquatic systems is essential to cover the growing demand of drinking water, especially in urban areas. However, the physico-chemical conditions of aquatic systems can be altered by a wide range of factors such as (i) the release of pollutants as a result of human activities (organic and inorganic contaminants), (ii) the presence of natural and engineered particles (inorganic particles, biocolloids and plastics), or (iii), the impacts of anthropogenic activities developed in urban areas (geothermal energy, constructions or landfills). All of these factors are of great concern because of their potential adverse effects on ecosystem functions, wildlife and human health.
The session is divided according with two main topics: (i) the effects of the presence of particles in environmental systems, and (ii), the consequences of anthropogenic activities on the physico-chemical conditions of urban water resources.
Main contributions will be focused on:
• The occurrence and fate of chemicals compounds of anthropogenic origin and particles in aquatic and terrestrial systems.
• The impacts of human related activities and actions on the physico-chemical conditions of water resources, especially in urban environments.
• Methods to detect, characterize, quantify and test the behaviour of particles in aquatic and terrestrial systems.
• Interactions between biocolloids, particles and solids
• Toxicity of products generated from biological disruption of pollutants in the presence of biocolloids and adverse effects of nanoparticles on microorganisms
• The effects of climate change on biocolloids and nanoparticles migration
• Public health risks associated with water and air polluted with biocolloids and nanoparticles.

During the last decades we have seen an exponential increase in new anthropogenic chemicals for all kinds of uses in society. Many of these are increasingly being detected at low levels in surface- and groundwater. Recent research on toxicity of chemicals such as per- and polyfluoroalkyl substances (PFAS), has raised concerns and led to stricter regulations in many countries. Contaminants such as PFAS, pharmaceuticals, pesticides, nanoparticles, plastics etc. may demonstrate low acute toxicity, but can still produce long-term adverse health effects even at very low levels of exposure. The ubiquitous presence of harmful, anthropogenic chemicals in the environment, some of which are “forever chemicals” that do not degrade naturally, requires immediate actions to reduce their release and spreading, better understand their transport and associated risks, and remove them from the environment.

These chemicals have produced many additional challenges for groundwater management, risk assessment and remediation. For many contaminants, the partitioning between different matrices such as the soil, groundwater and air as well as the interfaces between these phases is key to their mobility and fate as well as strategies for mitigation. Abiotic and biotic transformations and degradation influence persistence, partitioning between phases, mobility and risks. Many processes in both the groundwater and vadose zones need to be better understood and there is an urgent need for improved remediation and mitigation methods specifically designed for new contaminants. While contaminants of emerging concern are receiving attention in many places in e.g. Europe, North America and Australia, there are also large areas in the world where their occurrence and associated impacts on the environment and human health are poorly known. Finally, several challenges associated with the mitigation of traditional contaminants also remain.

This session seeks papers on process understanding through laboratory and field research, modeling, and site characterization to address new challenges and solutions associated with contamination of the soil-groundwater system by emerging contaminants and PFAS as well as unsolved challenges related to traditional contaminants.