* This is a solicited presentation and panel discussion session. Submitted contributions will be considered for a poster session

Hydrological process research and modelling play a key role in the management and sustainability of future water resources. This scientific session aims to explore the intricate interplay between scales of relevance in the context of future water resources management. By bringing together experts from surface hydrology, hydrogeology, eco-hydrology, and socio-hydrology, this session seeks to foster a dialogue on the pertinent scales that shape the availability, distribution, and utilization of future water resources.
The oral part of the session is composed of solicited presentations followed by a panel discussion. We solicit however poster contributions for a vibrating poster session.

Hydrology has significantly changed over the last few decades and is expected to continue evolving in the future due to climatic changes. With the increasing availability of observed streamflow data, remote sensing of evapotranspiration, water storage estimates, and the rapid advancement in global Earth system and land surface models, researchers now have a powerful toolset to understand hydrological changes on both regional and global scales.
However, numerous conflicting results exist between observational-based studies and global modeling results. These disparities highlight significant knowledge gaps in our understanding of hydrological processes in a changing climate. This session provides a valuable opportunity to address hydrological change topics in coordination with efforts from different regions worldwide to synthesize global-scale results.
We invite submissions covering a wide range of topics, including, but not limited to, the following topics:
1. Advanced techniques (ground observations and remote sensing) for more accurate estimation of hydrological components (precipitation, evapotranspiration, streamflow, and water storage changes) at catchment, regional, and global scales.
2. Responses and feedbacks of hydrological components to climate change and anthropogenic activities.
3. Projections of regional and global hydrological changes in the near and distant future.
4. Benchmarking hydrological modeling results using state-of-the-art observations.
5. Hydrological processes in hotspot regions such as the Tibetan Plateau, the Arctic, the Amazon and the regions with heavy irrigations.

Global climate change causes an increasing frequency and intensity of floods and droughts. Both are strongly linked and have the potential to reinforce each other. Floods and droughts cover the entire hydrological spectrum and share many similarities and links between the two types of extremes. Nevertheless, management strategies and technical compensation and mitigation measures are often thought only from one side of the extreme, like flood retention basins releasing the stored flood water within days instead of keeping it in the region. With the significant environmental, social and economic cost associated with such extremes, there is an increasing need for sustainable catchment management strategies that attenuate flow regimes, minimising the risk of flooding and ensuring a sustainable water supply and ecosystem resilience during drought periods.

This session addresses nature-based and technical strategies to mitigate the effects of hydrological extremes on the local water balance.

Nature-based solutions at the catchment scale work with or are inspired by nature to restore the natural functioning of our anthropogenically modified landscapes, providing both greater hydrological resilience to extreme events but critically also a host of additional benefits, particularly for biodiversity, climate, and society. As the popularity of nature-based solutions increases, trans-disciplinary research is required to: (1) determine what constitutes a nature-based solution; (2) maximise the effectiveness of such solutions and how they can be implemented alongside existing water management strategies; and (3) consider the social factors that are inherent in the successful implementation of nature-based solutions, overcoming the conflicts or barriers that may otherwise be associated with their implementation.

Technical solutions like managed aquifer recharge, mainly when applied in drinking water catchments, are often turned off during flooding events due to suspected contamination risks to the aquifer. In contrast, successful management of regional water resources seems to require approaches, tools, and management strategies that combine flood protection and drought prevention techniques, i.e., water retention, treatment, and infiltration in subsurface storage systems (ideally aquifers) for long-term, high-quality uses.

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

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

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

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

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

River deltas historically housed many of the Earth’s important ecosystems. The Anthropocene saw these grand terminals of the fluvial systems taking on a new role as now; they also support human lives while facing many intensifying pressures from natural systems, including floods, droughts, or salinity intrusion, that can heavily affect deltas’ Indigenous freshwater ecosystems while rendering the land inarable or even inhabitable. These negative impacts are exacerbated by human development and climate change induced sea level rise, increasing salinity and ground subsidence. Surface and groundwater resources for both domestic and agricultural purposes over overused, saline intrusion is increasing and land use for agriculture competes with nature and urbanization. How can we effectively meditate these impacts via Mitigation and adaptation? Or can we expect innovative strategies, such as using a water and food systems approach and Nature-based Solutions (NbS), to harvest the benefits of both effectively?
This session provides the opportunity for delta researchers to get updated on recent advancements of research related to adaptation and mitigation strategies in global mega deltas while providing ecosystem services (a.o. food supply) as they are taking on the rising climate hazards in the Anthropocene. We will discuss theoretical assessment studies, actual on-site interventions, innovative solutions and viewpoints of factors that may fuel/hamper the advancement of the delta research discourse. Contributions to addressing the following topics are welcome:
• Case studies reporting on-site observations.
• Theoretical assessments, including modelling of innovative mitigation and/or adaptation.
• Critical reviews of significant studies with clear focuses
• Reports of advancements in science-policy dialogues
• Innovative solution for adaptation and / or mitigation strategies

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

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

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

The MacGyver session focuses on novel sensors made, or data sources unlocked, by scientists. All geoscientists are invited to present:
- new sensor systems, using technologies in novel or unintended ways,
- new data storage or transmission solutions sending data from the field with LoRa, WIFI, GSM, or any other nifty approach,
- started initiatives (e.g., Open-Sensing.org) that facilitate the creation and sharing of novel sensors, data acquisition and transmission systems.

Connected a sensor to an Arduino or Raspberri Pi? Used the new Lidar in the new iPhone to measure something relevant for hydrology? 3D printed an automated water quality sampler? Or build a Cloud Storage system from Open Source Components? Show it!

New methods in hydrology, plant physiology, seismology, remote sensing, ecology, etc. are all welcome. Bring prototypes and demonstrations to make this the most exciting Poster Only (!) session of the General Assembly.

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

Understanding the complex interactions between soil-plant-atmosphere compartments and human activities is critical for ensuring the sustainable management and preservation of ecosystem functions and services. Global climate change and human activities threaten the functions and services of our terrestrial ecosystems. The complexity and holistic nature of the consequences have been difficult to assess so far, as simplified experimental approaches and long-term observations have methodological constraints and often focus on a very limited set of response variables.
Larger and more realistic experimental systems such as in situ lysimeters or ecotrons can supply a wide range of high quality continuous and high-resolution data sets on ecosystem services and functions in the Earths critical zone. Individual facilities and larger networks such as TERENO-SOILCan (lysimeter) or ANAEE’s ecotron experimental infrastructures provide a unique platform for a variety of interdisciplinary research to better understand the dynamic of ecosystems.
The session will focus on ecosystem research based on lysimeters and ecotron experiments, including model application. Additionally, we want to address upscaling approaches from lysimeter to landscape scale or between several types of ecosystem experimental infrastructures (e.g., lab, field, or control environments), uncertainty assessments, representativeness of lysimeter-scale observations, and comparability of water, and greenhouse gases flux to in situ measurements. We welcome contributions that (1) assess and compare terrestrial ecosystems functioning and services, (2) focus on water and solute transport processes, as well as greenhouse gases within the soil-plant-atmosphere continuum, including processes such as non-rainfall water inputs (i.e., dew, fog, soil water vapor adsorption), (4) develop new techniques for analyzing lysimeter and ecotron observations, (5) including ecosystem or hydrological modelling approaches that use in-situ observations from lysimeters or ecotrons.

Ensuring safe water supply for human and environment, and protecting them from water hazards have become more challenging due to intensified impacts of climate change, globalization, and population growth. Hydrological knowledge is needed more than ever to address water security issues. However, scientific knowledge on resilience and water security is fragmented in discipline, people, and place. There is a substantial lack of synthesis and easily digestible scientific messages among hydrologists, across disciplines and from scientists to practitioners, decision-makers and the general public. Hence, there is a need for the hydrological research community to better link local hydrological research with global patterns of the water cycle, and further, to provide science-based water-centric decision support.

Therefore, the International Association of Hydrological Sciences (IAHS) is dedicating the next scientific decade to science for solutions. The short name is HELPING, and stands for Hydrology Engaging Local People IN one Global world. It aims to identify local water problems in holistic/system analyses (i.e., linking local and global scales, disciplines and needs, and connecting the dots), search for solutions, be bold and push boundaries to make an impact and connect people across and within regions (e.g., Global North, Global South, North-North, South-South) and provide synthesis to answer the needs of society for sustainable development, safety and security. The topic and vision of the new decade was an outcome of several on-line interactions and workshops during 2023 using a strategic planning approach, as summarised and documented at https://iahs.info/. To date, some 30 working groups have been suggested by the global hydrological community.

This session invites contributions related to the three major themes of HELPING, which all aim at understanding hydrological diversity and integrating knowledge across scales and regions to overcome the water crisis by:
(1) recognising global and local interactions;
(2) finding holistic solutions for water security;
(3) applying cross-cutting methods for facilitation, e.g. science communication, integrating new technology and fostering local co-creation processes.
In particular, we encourage submissions from early career scientists, suggested working groups, and studies that include transdisciplinary and applied experience for solving environmental and societal challenges related to water.

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 and documenting choices along the modelling chain and
(8) Uncertainty propagation along the modelling chain
(9) Communicating model results and their uncertainty to end users of model results
(10) Evaluating implications of model limitations and identifying priorities for future model development and data acquisition planning

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

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

Beyond the presentation of research findings, this session will also focus on advancements in laboratory and modelling techniques, highlighting improvements in accuracy, complexity, and spatial-temporal resolution. Cutting-edge modelling approaches tailored to simulate the intricate transport dynamics of plastics in aquatic environments will be showcased.

Through engaging discussions, the session aims to enhance our comprehension and predictive capabilities, while also identifying unresolved questions and paving the way for future research endeavors in this vital area of study.

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

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 fresh water supply. A considerable part of the world’s population depends on this water supply, around 26% live directly in the mountains and 40% live downstream of rivers originating in the mountains. The large elevation ranges and the heterogeneity of elevation-dependent hydro-meteorological conditions make mountains particularly sensitive to climate variability and change, but therefore also unique areas for identifying and monitoring the effects of global change.
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 hydrological conditions (in either mountain surface and/or ground water systems).
• Methods for differentiating climatic and anthropogenic drivers of hydrological change in the mountains.
• Modelling approaches to assess mountain hydrological change.
• Evolution, forecasting and impacts of extreme events.
• Case studies on adaptation to changing mountain water resources availability.

Water is a strategic issue in drylands, where ecosystems and their inhabitants strongly rely on the scarce and often intermittent water availability or its low quality. The characteristics of drylands increase their vulnerability to climate change and susceptibility to the impact of short- to long-term extreme events and processes, such as floods, droughts, and desertification. These events can reshape the landscape through the mobilisation of surface sediments, deposits of which preserve archives of past Earth system states, including changes in the extent of deserts. Over the last century, anthropogenic modifications of all kinds and intensities have affected surface conditions. In drylands and Mediterranean hydrosystems, agricultural water use is constantly increasing threatening the sustainability of the surface and groundwater reservoirs, and their hydrology is then continuously evolving. Nevertheless, the study of hydroclimatic processes in drylands remains at the periphery of many geoscientific fields. A proper understanding of the hydrological, hydrometeorological and (paleo)climatic processes in these regions is a cornerstone to achieving the proposed sustainable development goals we set for the end of this century.

This session welcomes contributions from scientific disciplines addressing any of the 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. We will address hydrological issues across global drylands, and devote a section of our session to a geographical focus on the Mediterranean region to analyse the changes in hydrologic processes and fluxes unique to that region.

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.

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.

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

The Critical Zone (CZ) – the permeable near-surface layer of the Earth where the lithosphere, hydrosphere, atmosphere, and biosphere interact – is the place where cycles of carbon, nutrients, water and other biogeochemical processes intersect with ecosystems and society. Investigating the form and functioning of the CZ requires that insights from geology, hydrology, ecology, geochemistry, atmospheric science and other disciplines are integrated in a transdisciplinary manner. One successful approach to CZ research has been the development of intensively instrumented study areas, known as CZ observatories. Networks of observatories and interlinked thematically-focused projects have evolved to capitalize on advances possible through multifaceted collaborations across larger spatial scales. Processes that shape the critical zone also span wide ranges of temporal scales, from vegetation on seasonal timescales, to soil development and landscape evolution over thousands to millions of years. Because all of these processes together shape the critical zone and affect how it functions, bridging gaps between short term processes and longer-term environmental change is essential for understanding landscapes and maintaining their ability to sustain life.

This session will highlight the cutting edge of CZ science across spatial and administrative scales, from project, to observatory, to network levels. Submissions may also explore coupling across temporal scales, integrating relatively rapid processes with the longer-term evolution of the critical zone. Submissions are solicited that focus on integration of observations and modeling; hydrologic dynamics; geoecological interactions; biogeomorphology, mineral weathering and nutrient cycling; the rhizosphere; the societal relevance of CZ science; and other examples of how CZ research is evolving with new knowledge to face the challenges of our changing world. Contributions from early-career scientists are particularly encouraged.

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

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 functioning of catchments. Traditionally, catchment hydrology has been centered around surface runoff, which is readily observable. But at the same time, invisible below ground processes entailing the storage dynamics and flows of water are still underexplored. This includes subsurface runoff, as well as feedbacks of subsurface processes to the surface and the specific role of soil moisture in shaping these fluxes. This session aims to bring together contributions on the following topics and to address gaps in observations, models, and understanding of hydrologic systems:

- Identifying, tracing, and modeling subsurface runoff generation at the catchment scale.

- Factors and mechanisms controlling subsurface water storage and fluxes

- How soil moisture measurements at different scales can be used to improve process understanding, models, and hydrologic theory

- Interactions of surface and subsurface hydrologic processes

Large data samples of diverse catchments provide insights into the physiographic and hydroclimatic factors that shape hydrological processes. Such data sets enable research on 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 that advance the characterization, organisation, 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?
2. Catchment similarity and regionalization: Can currently available global datasets be used to define hydrologic similarity? How can information be transferred between catchments and to data-scarce regions?
3. Modelling capabilities: How can we improve process-based and machine learning modelling by using large samples of catchments?
4. Testing of hydrologic theories: How can we use large samples of catchments to test and refine hydrologic theories and asses their general validity?
5. Identification and characterisation 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?

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

Anthropogenic activities like agriculture and wastewater discharge have resulted in the degradation of groundwater and surface water quality with severe implications for both human and environmental health. There is an urgent need to mitigate these impacts on water quality crucial for maintaining the ecological, recreational, and industrial functions of water resources.
Water quality is typically monitored and assessed at the catchment scale. Understanding the underlying processes and causal relationships remains challenging due to the complex interplay of hydrologic, biogeochemical, and temporal factors. This large scale of monitoring does not always match the scale of mitigation measures to minimize anthropogenic impact on water quality.
Data-driven statistical analysis of discharge and concentration time series at catchment outlets offers valuable insights into the scaling of processes and the effectiveness of measures. Long-term, high-frequency, and multi-site data sets can inform experimental and modeling studies, enabling us to move from patterns to processes and gain a deeper understanding of solute and particulate mobilization, retention, and export mechanisms.
This session brings together contributions on the assessment of mitigation measures, analysis of solute and particulate export dynamics, and catchment modeling to optimize mitigation placement.

Quantifying and understanding the impacts of environmental change on water quality and availability across space and time is critically important for ensuring that there is enough water of suitable quality to meet human and ecosystem needs now and in the future. Consequently, there is an urgent need for tools such as models, remote sensing, machine-learning and artificial intelligence algorithms that can anticipate these impacts and address the resulting environmental changes. These assessments in turn facilitate more effective water management that safeguards the critical ecosystem goods and services provided by freshwater resources. In addition, some of these tools, within both Bayesian and frequentist paradigms, enable consideration of prediction reliability, relating uncertainties to a decision makers’ attitudes and preferences towards risks, all while accounting for the uncertainty related to our system understanding, data and random processes. We seek contributions that apply modeling and other approaches to:
• investigate climate change impacts on water quality and quantity from local to global scales, including climate impact attribution studies
• quantify and couple supply and demand in support of water management including vulnerability assessment, scenario analysis, indicators, and the water footprint
• project future water supply and demand in the context of a changing climate, land use, population growth, and other potential drivers of change
• quantify the uncertainty of model predictions (due to data, model structure and parameter uncertainty)
• interpret and characterize uncertainties in machine-learning and data mining approaches that learn from large, possibly high-resolution data sets
• address the problem of scaling (e.g. disparity of scales between processes, observations, model resolution and predictions)
• test transferability and generalizability of findings
• assess water quality and quantity in either data-rich or data-sparse environments
• involve stakeholders in model development and maximise the use of expert knowledge to inform risk analysis and decision support, incl. monitoring, reporting and catchment management
• assess robustness in water quality and quantity hotspots

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

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

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

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

This session welcomes contributions from field, laboratory and modelling studies that aim to advance our understanding of river network and catchment-scale plastic transport and accumulation processes. We are soliciting studies dedicated to all plastic sizes (macro, micro, nano) and across all geographic settings. We are especially encouraging studies that can link plastic accumulation and transport to catchment-wide hydrological, ecological or geomorphological processes that we can better understand where, when and why plastics accumulation takes place in aquatic-terrestrial environments.

In this session, we explore the current state of knowledge and activities on macro-, micro- and nanoplastics in freshwater systems, focusing on aspects such as:

• Transport processes of plastics at catchment scale;
• Source to sink investigations, considering quantities and distribution across environmental matrices (water and sediment) and compartments (water surface layer, water column, ice, riverbed, and riverbanks);
• Plastic in rivers, lakes, urban water systems, floodplains, estuaries, freshwater biota;
• Effects of hydrological extremes, e.g. accumulation of plastics during droughts, and short-term export during floods in the catchment;
• Modelling approaches for global river output estimations;
• Legislative/regulatory efforts, such as monitoring programs and measures against plastic pollution in freshwater systems.

The occurrence of pathogens and of an exponentially increasing number of contaminants in freshwater and estuary environments pose a serious problem to public health. This problem is likely to increase in the future due to more frequent and intense storm events, the intensification of agriculture, population growth and urbanization. Pathogens (e.g., pathogenic bacteria and viruses, antibiotic resistance bacteria) are introduced into surface water through the direct discharge of wastewater, by the release from animal manure or animal waste via overland flow, or, into groundwater through the transport from soil, which subsequently presents potential risks of infection when used for drinking, recreation or irrigation. Contaminants of emerging concern are released as diffuse sources from anthropogenic activities, as discharges from wastewater treatment plants (e.g., trace organic contaminants, PFAS), or occur due to microbial growth (e.g. cyanotoxins), posing a burden on human health. So far, the sources, pathways, fate and transport mechanisms of fecal indicators, pathogens and emerging contaminants in water environments are poorly understood, and thus we lack a solid basis for quantitative risk assessment and selection of best mitigation measures. Innovative, interdisciplinary approaches are needed to advance this field of research. In particular, there is a need to better understand the dominant processes controlling fecal indicator, pathogen and contaminant fate and transport at larger scales.
This session aims to increase the understanding about the dominant processes controlling fecal indicator, pathogen and contaminant fate and transport at larger scales. Consequently, we welcome contributions that aim to close existing knowledge gaps and include both small and large-scale experiments, with the focus on
- the fate and transport of fecal indicators, pathogens, emerging contaminants including persistent and mobile organic trace substances (e.g. antibiotic resistance bacteria, cyanotoxins, PFAS) in rivers, soils, groundwater and estuaries
- Hydrological, physically based modelling approaches
- Methods for identifying the dominant processes and for transferring transport parameters of fecal indicators, pathogens and contaminants from the laboratory to the field or catchment scale
- Investigations of the implications of contamination of water resources for water safety management planning and risk assessment frameworks

Assessing the impact of climate variability and changes on hydrological systems and water resources is crucial for society to better adapt to future changes in water resources, as well as extreme conditions (floods and droughts). However, important sources of uncertainty have often been neglected in projecting climate impacts on hydrological systems, especially uncertainties associated with internal/natural climate variability. From one model to another, or from a single model realization to another, the impact of diverging trends and sequences of interannual and decadal variability of various internal/natural climate modes (e.g., ENSO, NAO, AMO) could substantially alter the impact of human-induced climate change on hydrological variability and extremes. Furthermore, model findings may contrast with insights that global satellite data provide, e.g. observations of hydrological change often do not support dry-gets-dryer and wet-gets-wetter patterns that global climate models suggest. Therefore, we need to improve both our understanding of how internal/natural climate patterns affect hydrological variability and extremes, and how we communicate these impacts. We also need to better understand how internal/natural climate variations interact with various catchment properties (e.g., vegetation cover, groundwater support) and land-use changes altering them. In this direction, storylines of plausible worst cases, or multiple physically plausible cases, arising from internal climate variability can complement information from probabilistic impact scenarios. In addition, a comparison of satellite data and model output can help close the gap in understanding wetting and drying patterns at the continental scale.

We welcome abstracts capturing recent insights for understanding past or future impacts of internal/natural climate variability on hydrological systems and extremes, as well as newly developed probabilistic and storyline impact scenarios. Results from model intercomparisons using large ensembles are encouraged. We also solicited presentations on improving our observing system (e.g. via new retrieval approaches, data assimilation, or developing new sensor systems) and on developing modelling frameworks.

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

Catchments are complex systems responding to external factors (e.g. changes in climate) on a variety of timescales due to complex interactions and feedbacks. Many existing models and methods poorly represent the responses of hydrological systems to changes in boundary conditions (e.g. climatic change), affecting the reliability of their results. 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 hydrological systems need to be disentangled and understood, and generalizable insights need to be sought. Such insights can originate both from site-specific investigations or from studies that use large datasets and/or models, and improve hydrological predictions under changing conditions and in ungauged locations.
This session covers themes such as (but not limited to):
1. Improved process understanding through field and modeling applications;
2. Better understanding of hydrological and/or biophysical processes related to long-timescale climate shifts potentially contributing to shifts in hydrologic response;
3. Understanding and quantifying drivers of catchment similarity and how that may be used to transfer knowledge in space and time;
4. Studies of hydrological regularities (e.g. the Budyko hypothesis) for predictions under changing conditions;
5. Understanding and quantifying catchment multi-annual “memory”;
6. Data-based and modelling studies aiming to better understand and simulate the response of hydrological systems to climatic variability and change;
7. Efforts to improve the realism of hydrological projections under future climate scenarios.

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. Groundwater is an important part of that cycle, providing freshwater to humans and ecosystems; while aquifers may span political and natural boundaries, our large-scale understanding of groundwater processes and the connection between ground and surface waters still needs to be improved.

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 modelling;

(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.

(v) identification of controls on groundwater processes across large domains and transboundary and inter-catchment assessments of groundwater processes;

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

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.

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

The management of water systems is subject to a multitude of challenges on different spatial and temporal scales, ranging from hydrological extremes to uncertainties in planning and decision-making. Both aspects relate to the probability distributions of relevant variables in time and space, exploring the full range of the distributions and the extremes. This integrated session recognizes the interconnected nature of these challenges, and seeks to merge insights from two distinct yet interrelated domains: spatio-temporal analysis and uncertainty management in water networks. Spatio-temporal analysis can be applied to enhance prediction and management of hydrological extremes, in particular floods, droughts, and compound hazards. Hydrological challenges often manifest in spatial, temporal, or spatio-temporal dimensions. Leveraging technological advancements such as remote sensing, the first block of this session explores the integration of diverse data sources into hydrological models and analyses. Statistical methods and Machine Learning (ML) are pivotal, addressing challenges posed by data scarcity and the dynamic nature of hydrological events. This emphasis extends to spatio-temporal analyses, vital for refined risk assessment and early management strategies in the face of increasing hydrological variability.

The deterministic paradigm has traditionally underpinned hydraulic modeling and planning of drinking water, wastewater and urban drainage networks. While methods like calibration and scenario approaches address some uncertainties, an evolving understanding of uncertainties demands a more comprehensive approach. This second block of this session focuses on the treatment of uncertainty in planning, modeling, and decision-making for water networks, encompassing drinking water, wastewater, and urban drainage.

This integrated session provides a platform for interdisciplinary approaches, aiming at hydrologists, statisticians, and water system experts. Combining spatio-temporal analysis and uncertainty management brings together complementary methodologies and applications for resilient water systems in both urban and rural contexts.

Deep Learning has seen accelerated adoption across Hydrology and the broader Earth Sciences. This session highlights the continued integration of deep learning and its many variants into traditional and emerging hydrology-related workflows. We welcome abstracts related to novel theory development, new methodologies, or practical applications of deep learning in hydrological modeling and process understanding. This might include, but is not limited to, the following:

(1) Development of novel deep learning models or modeling workflows.

(2) Probing, exploring and improving our understanding of the (internal) states/representations of deep learning models to improve models and/or gain system insights.

(3) Understanding the reliability of deep learning, e.g., under non-stationarity and climate change.

(4) Modeling human behavior and impacts on the hydrological cycle.

(5) Deep Learning approaches for extreme event analysis, detection, and mitigation.

(6) Natural Language Processing in support of models and/or modeling workflows.

(7) Uncertainty estimation for and with Deep Learning.

(8) Applications of Large Language Models (e.g. ChatGPT, Bard, etc.) in the context of hydrology.

(9) Advances towards foundational models in the context of hydrology and Earth Sciences more generally.

(10) Exploration of different optimization strategies, such as self-supervised learning, unsupervised learning, and reinforcement learning.

The complexity of hydrological systems poses significant challenges to their prediction and understanding capabilities. The rise of machine learning (ML) provides powerful tools for modeling these intricate systems. However, realizing their full potential in this field is not just about algorithms and data, but requires a cooperative interaction between domain knowledge and data-driven power. This session aims to explore the frontier of this convergence, examining how prior understanding of hydrological and land surface processes or causal representations can be incorporated into data-driven models, and conversely, how ML might enrich our causal or physical understanding of system dynamics and mechanisms.

We invite researchers working at the intersection of explainable ML/AI and hydrological or Earth system sciences to share their methods, results, and insights. Submissions are welcome on topics including, but not limited to:

- Explainability and transparency in ML/AI modeling of hydrological and Earth systems;
- Integration of hydrological processes and knowledge in ML/AI models;
- Multiscale and multiphysics representation in ML/AI models;
- Causal representation learning in hydrological and earth systems;
- Strategies for balancing model performance and interpretability;
- Leveraging insights from data science and XAI to deepen physical understanding;
- Data-driven approaches to causal analysis in hydrological and Earth systems;
- Challenges, limitations, and solutions related to hybrid models and XAI.

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

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

This session invites contributions that discuss advances, both in theory and/or application, in (Bayesian) UA methods and methods for SA applicable to all Earth and Environmental Systems Models (EESMs), which embrace 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) Novel methods for spatial and temporal evaluation/analysis of models
3) Novel approaches and benchmarking efforts for parameter estimation
4) Improving the computational efficiency of SA/UA (efficient sampling, surrogate modelling, parallel computing, model pre-emption, model ensembles, etc.)
5) The role of information and error on SA/UA (e.g., input/output data error, model structure error, parametric error, regionalization error in environments with no data etc.)
6) Methods for evaluating model consistency and reliability as well as detecting and characterizing model inadequacy
7) Analyses of over-parameterised models enabled by AI/ML techniques
8) Robust quantification of predictive uncertainty for model surrogates and machine learning (ML) models
9) Approaches to define meaningful priors for ML techniques in hydro(geo)logy

The invited speaker of this session is Francesca Pianosi (University of Bristol).

Heavy precipitation in small- to medium-sized catchments leads to catastrophic damage due to hazards including: surface water floods (prior to water entering drainage networks or streams) or flash floods, erosion and sediment transport, debris flows and shallow landslides.
Improving the anticipation of such hazards is crucial for efficient crisis management. However, many challenges still exist regarding their temporal and spatial predictability. On one hand, the fast evolution of triggering rainfall events, the lack of appropriate observations, the high variability and non-linearity in the physical processes can induce a lot of uncertainty. On the other hand, the coexistence of several hazards, the high variability of societal exposure, as well as the complexity of societal vulnerability make it very challenging to assess the overall potential risks.
This session aims to illustrate current advances in monitoring, modeling, and short-range forecasting of all heavy rainfall induced hazards and risks (e.g., surface water floods, flash-floods, and geomorphic hazards). Contributions on the following scientific themes are specifically expected:
- Monitoring and nowcasting of heavy precipitation events based on radar and remote sensing (satellite, lightning, ..), to complement rain gauge networks.
- Short-range (0-6h) heavy precipitation forecasting based on Numerical Weather Prediction models, with a focus on seamless forecasting strategies, and ensembles for the representation of uncertainties.
- Understanding and modeling of surface water floods, flash floods, and geomorphic processes, at appropriate space-time scales.
- Development of integrated hydro-meteorological forecasting chains and new modeling approaches for predicting short-rainfall-induced hazards in gauged and ungauged basins.
- New direct and indirect (proxy data) observation techniques and strategies for the observation or monitoring of rainfall-induced-hazards, and the validation of forecasting approaches.
- Risk modeling and forecasting approaches, including inundation mapping, damages modeling, and/or other impact-based approaches.
- Assessing changes of rainfall induced hazards due to the coexistence with other types of hazards (e.g. forest fires).
- Early warning systems for rainfall-induced hazards and their verification.

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

This session addresses statistical, remote sensing 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 and are invited to submit to this session. 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 research 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-generation).

The focus of this session will be on bringing the expertise from different fields together as well as exploring differences, similarities, problems and solutions between forecasting systems for varying hazards including climate emergency. Real-world case studies of system implementations - configured at local, regional, national, continental and global scales - will be presented, 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, and those working in multi-disciplinary projects (e.g. EU Horizon Disaster Resilience Societies).

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

Co-organized by ESSI2/GI2, co-sponsored by WMO

This session brings together HS4.6 “Improving hydro-climatic services for the water-related sectors: from S2S forecasting to climate projections, to management and policy” and HS1.2.4 “From observations to action: role of data services in hydrological research and management”.

We present a forum for discussing ideas, efforts and challenges in developing data products and hydro-climate services that aim to support water-related sectors. The session will bring together research scientists and operational managers in the fields of hydrology and climate and will showcase real-world applications of datasets, products, and services for research purposes and/or to tackle societal needs.
This session thus aligns with the goal of the Ninth Phase of the UNESCO Intergovernmental Hydrological Programme Strategic Plan (IHP IX; 2022 - 2029), which puts science, research and management into action for a water secure world. The contributions of this session will cover the following topics:

1. Data - observations, forecasts, projections:
- metadata, quality assurance,
- downscaling,
- advances in sub-seasonal, seasonal and decadal hydrological predictions,  
- seamless forecasting techniques and applications,
- data-driven and process-based approaches,
- extreme events prediction.
2. Databases and services:
- improvement in database services,
- operational hydro-climate products and services,
- tools and platforms for data exchange and exploration,
- collaborative and interoperable data platforms for better decision-making.
3. From data to action: role of data and climate services for societal needs
- data-driven studies and projects that aim to support decision-making and policy-making,
- 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,
- approaches integrating weather, climate and / or socio-economic information into decision-making frameworks,
- perspectives on forecast value for end users.

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

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

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

Water governance predominantly operates at national scales. This underscores the necessity for national or country-scale hydrological models. The inclination towards scales larger than single catchments or aquifers encounters distinct challenges because large spatial grids may often compromise on spatial resolution. Furthermore, their computational demands can make them less suited for specific national applications, especially when contending with the unique nuances of each country's water governance policies and regulations. This session endeavors to spotlight the critical role of national-scale hydrological models in the precise assessment and strategic management of freshwater resources in concert with national governance frameworks. We invite submissions from the hydrological community focusing on the evaluation of freshwater resources at a national scale, the application of hydrological models for national-scale water resource management, and the integration of observations with models to address country-specific freshwater issues. Furthermore, developers of national-scale hydrological models are particularly encouraged to share their insights and advancements.

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.

Water sustains societies, economies and ecosystem services locally and 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.

Human society and the natural environment are profoundly intertwined. Human activities such as food and energy production and consumption can directly impair environmental sustainability by causing local water stress, regional air pollution, and global climate change. At the same time, the natural environment plays a vital role in providing essential resources and services for human survival, such as water, energy, and food, and can have severe feedbacks on human society. For instance, changes in hydrological dynamics induced by climate change can threaten energy and food security by causing spatial and temporal mismatches between water availability and the demand for water in agriculture and energy production. This amplifies challenges at the water-energy-food-environment nexus, which are further intensified by rapid urbanization, soaring economic development, increasing energy and food demand, and growing competition for water across sectors. If unaddressed, these challenges can contribute to a destructive positive feedback loop that is threatening to aggravate resource scarcity, environmental degradation, and social inequality. Effectively navigating the water-energy-food-environment (WEFE) nexus under social and climate change requires holistic approaches that consider the interdependencies and feedbacks within and across these systems. It necessitates balancing competing demands, optimizing resource efficiency, promoting sustainable practices, maximizing synergies, and fostering collaboration among various stakeholders.

We invite contributions evaluating the vulnerability, resilience, and adaptive capacity of WEFE nexus systems in the face of global change that particularly have real-world implications or are based on real-world practices. We further invite contributions focusing on harmonization, planning, and equitable allocation within the nexus system that can provide insights for policy-making towards a more sustainable development of resource systems through nexus management. We also welcome successful regional case studies or experiments that focus the interactions between two elements of the water-energy-food-environment nexus with a focus on sustainability.

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, and 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 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 feedback 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) which 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/

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). LULC changes can emerge directly from anthropogenic interventions, or indirectly as the result of climate change, determining different levels of impact on socio-ecological systems. Integrated approaches are needed to assess the impact of LULC changes on the whole hydrological cycle (e.g. streamflow, groundwater quantity and quality, evaporation and transpiration, soil moisture, and rainfall interception) and associated ecosystem services. Indeed, changes to these elements can possibly lead to non-local and non-linear effects on WES and their dynamics in socio-ecological systems, which need to be analysed from multiple perspectives, such as ecohydrology as well as socio-hydrology, to inform effective and equitable water resource management.

This session welcomes both ecohydrology and socio-hydrology studies that address the impacts of LULC changes on all water resources, hydrological processes, and associated WES, such as flood regulation, moisture recycling, temperature regulation, and food provisioning. More specifically, we welcome studies including, but not limited to:

• Advances in the quantification of hydrological impacts of LULC changes through ecohydrological and socio-hydrological modelling and experimental data
• Disentanglement of LULC change impacts on water resources (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
• Socio-hydrological and Hydro-social approaches dealing with land, water, and ecosystem management, aiming also to highlight feedback loops between social and bio-geophysical dynamics

Individual and collective human behavior is increasingly recognized as a critical determinant of our ability to cope with climate change, increasing water scarcity, and more frequent extreme events, as sectoral resource demands and adaptation challenges grow. Yet, severe uncertainties characterize our forecasts of societal pathways, behaviors, and vulnerabilities, and the future trajectories of coupled human-water systems remain insufficiently understood. The increasing availability of data, analysis tools, and interdisciplinary perspectives offers novel entry points for a more fertile engagement between hydrological and social sciences to address these limitations.
This session welcomes 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. We aim to 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 data-driven, conceptual or model-based research; and 3) shed light on the added value of coupled human-water systems analyses for water resources management, risk management, and adaptation design.
The session will provide a forum for inter- and transdisciplinary exchange around emerging approaches to analyze growing hydrological challenges, human adaptation, and human-water feedbacks across multiple sectors (e.g., irrigated land-use, urban water demand, reservoir management, etc.) and scales (from the plot level to entire watersheds and beyond) in support of water management, adaptation and governance. These approaches include, but are not limited to, coupled human-water systems, socio-hydrological, hydro-economic, hydro-social, multi-sector, or data-driven (e.g.: machine learning, data mining, econometric, and remote sensing) methods. We specifically welcome contributions which reflect how these approaches support the new IAHS decade HELPING Science for Solutions aim and contributes to the newly formed IAHS commission on Human-Water Feedbacks (ICHWF).

This session welcomes abstracts that consider how to observe, analyse and model feedbacks of people and water, and the effects of social and environmental changes on hydrological systems. It is organised by the new International Commission on Human-Water Feedbacks (ICHWF) of IAHS that is providing a home for interdisciplinary research on the dynamics of human-water systems after the end of the Panta Rhei decade in 2023.
Examples of relevant topics include:
• Observations of human impacts on, and responses to, hydrological change
• Interactions of communities with local water resources
• Hydrological models that include anthropogenic effects
• Interdisciplinary qualitive and quantitative methods including theoretical models to isolate, conceptualize and/or simulate feedbacks in human water systems
• Creation of databases describing hydrology in human-impacted systems
• Data analysis and comparisons of human-water systems around the globe and especially in the global south
• Human interactions with hydrological extremes, i.e. floods, droughts and water scarcity
• The role of gender, age, and cultural background in the impacts of hydrological extremes, risk perception, and during/after crises and emergencies

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

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

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

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

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

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

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

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

Water utilities and municipalities must embrace technological innovation to address the 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, modeling 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 behavioral analysis, artificial intelligence for water applications (including also more recent trends such as large language models and physics informed machine learning), 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.

This session celebrates 20 years of soil moisture remote sensing at the EGU General Assembly. We invite presentations concerning the past, present and future of soil moisture estimation, including remote sensing, field experiments, land surface modelling and data assimilation and soil moisture reference networks and fiducial reference measurements (FRMs).
Over the past two decades, the technique of microwave remote sensing has made tremendous progress to provide robust estimates of surface soil moisture at different scales. From local to landscape scales, several field or aircraft experiments have been organised to improve our understanding of active and passive microwave soil moisture sensing, including the effects of soil roughness, vegetation, spatial heterogeneities, and topography. At 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 an accurate quantification of the soil moisture at regional and global scales. Building on the legacy of these mission operational programmes like Copernicus but also novel developments will further enhance our capabilities to monitor soil moisture, and they will ensure continuity of multi-scale soil moisture measurements on climate scales.

We encourage submissions related to soil moisture remote sensing, including:
- Global soil moisture estimation from coarse resolution active and passive sensors.
- High spatial resolution soil moisture estimation based on e.g. Sentinel observations, GNSS reflections, or using novel downscaling methods.
- Future mission concepts.
- Field experiment, theoretical advances in microwave modelling and calibration/validation activities.
- 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.
- Progress towards the estimation of SI-traceable uncertainty budgets including uncertainty characterization across scales.
- Soil moisture reference networks.
- Application of satellite soil moisture products in scientific and operational disciplines.

With the increased attention of society to climate change, drought and flood early warning systems, ecosystem monitoring, and biodiversity conservation, and reaching a sustainable future, the demand for estimating, modelling, mapping, and forecasting evapotranspiration (ET) as the key water flux at the interface of soil, vegetation and atmosphere has expanded. New techniques such as artificial intelligence (AI), data fusion, sharpening algorithms, and the combination of physical- and process-based models with empirical/statistical methods and machine learning are cutting-edge for bridging different scales while considering and communicating method-specific uncertainties. New techniques over all spatial scales and the variety of space/airborne sensors introduce new horizons to quantify ET over various land covers. Cloud computing platforms provide scientists and researchers with the pivotal tools, data, and computing resources to model and analyze hydrological parameters like ET while offering scalability, efficiency, and collaboration opportunities. Scale dependencies of the various approaches as well as strategies to handle uncertainties, systematic biases and representativity of the estimates need further detailed evaluation. Remote sensing of ET supports evidence-based decision-making, helps in addressing water-related challenges, contributes to sustainable water management practices, and better informs managers, end-users, and the community.

In our session on ET derived from point scale such as sap flow measurements to large-scale derivations using remote sensing, we welcome your research findings, commentary pieces and debates on
* analysing trends as well as spatial and temporal patterns in ET data
* application of AI, cloud computing and technology advancement
* fusion and cross-scale comparisons of remote sensing, modelled and ground-based derived ET including their respective uncertainties and systematic errors
* validation, calibration and upscaling challenges and improvements
* future directions of ET determinations from local to continental scale

Snow constitutes a freshwater resource for over a billion people world-wide. A 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 of being dramatically reduced, affecting not only the water supply but also the ecosystems of these areas. Therefore, understanding seasonal snow dynamics, its possible changes and their implications have become crucial for water resources management.

Remote sensing has been used for decades as the primary technique to monitor snow properties and their hydrological implications across scales. The recent technical advances favoured the study of snow properties at finer spatio-temporal resolution, helping to understand better the snow dynamics (e.g., the interaction of snow with small-scale, quick snow changes within a day, rain on snow events, snow-vegetation interaction).

This session focuses on studies linking the use of remote sensing of seasonal snow to hydrological applications with the aim of: (i) better quantifying snow characteristics (i.e., snow grain size, snow depth, albedo, pollution load, snow specific area, liquid water content and snow density), (ii) understanding snow-related processes and dynamics (snowfall, melting, evaporation, wind redistribution and sublimation), (iii) improving snow modelling and, (iv) assessing snow hydrological impacts and snow environmental effects. Works covering techniques and data from different technologies (time-lapse imagery, laser scanners, radar, optical photography, thermal and hyperspectral technologies, or other new applications), different spatial scales (from the plot to the global), and temporal scales (from instantaneous to multiyear), are welcome.

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

Monitoring these resources plays a key role in assessing water resources, understanding water dynamics, characterising and mitigating water-related risks and enabling integrated management of water resources and aquatic ecosystems.

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

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

Traditional instruments contribute to long-term water level monitoring and provide baseline databases. Scientific applications of more complex technologies like Synthetic Aperture Radar (SAR) altimetry on CryoSat-2, Sentinel-3A/B and Sentinel-6 missions are maturing, including the Fully-Focused SAR technique offering very-high along-track resolution. The launched SWOT mission will open up many new hydrology-related opportunities when the data is calibrated, validated and released. We also receive submissions of preparation studies for Sentinel-3 Next Generation and CRISTAL and other proposed missions such as Guanlan, HY-2 and SmallSat constellations such as SMASH, and covering forecasting.

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

The hydrological cycle involves the continuous movement of water on, above, and below the surface of the Earth. In general, hydrological cycle components (e.g., precipitation, evaporation, water storage, and runoff) are characterized by large temporal and spatial variability. Accurate monitoring of various hydrological cycle components and the development of hydrological models are important for improving our understanding of hydrological processes. Acquiring this understanding is a crucial prerequisite to ameliorate resource management, optimize the development of infrastructure, and adjust land use practices to changing climate conditions and hazards such as floods and droughts.

With significant development of sensor technology and sharply growing platforms in past decades, remote sensing offers an enhanced capability to monitor various hydrological cycle components at different temporal and spatial scales to complement, or even replace, in situ measurements. Considerable efforts have been made to explore the potential of remotely sensed data from a vast range of different platforms (e.g., satellite, airborne, drone, ground-based radar) and sensors (e.g., optical, infrared, microwave) in advancing hydrology research, particularly in poorly gauged and ungauged regions. The application of remote sensing in hydrology is expected to increase with enhanced recognition of its potentials and continuous development of advanced sensors (e.g., new satellite missions) and retrieval methods (e.g., innovative machine learning and data assimilation techniques).

This session aims to present and discuss recent advances in the remote sensing of hydrological cycle components, their application in hydrological modeling, and their synthesis with in-situ data. We particularly welcome contributions that explore:
- The performance of remotely sensed data in multi-variable calibration and spatial evaluation of hydrological models
- The added-value of spatially downscaling remotely sensed data in improving hydrological modeling
- The combination of in-situ and remotely sensed data to analyze water cycle components and hydrological extremes such as floods and droughts
- The development of novel methods to gather in-situ benchmark data to combine with remotely sensed approaches
- Synthesized advances of remote sensing applications in hydrology, in natural and anthropized ecosystems

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The atmospheric precipitation process comprises an ensemble of a wide variety of hydrometeors that result from the complex atmospheric processes of nucleation, accretion, melting and interactions. Rainfall reaches the ground surface with varying intensity, drop size and velocity distributions, which depends on the specific site climatology and the event type and characteristics. The terminal velocity of each raindrop is a function of its size and affects the kinetic energy transferred to the soil. These rainfall features are assessed in situ by employing raingauges and disdrometers, but accurate measurements require suitable adjustments for instrumental and environmental biases.
Appropriate knowledge and ability to reproduce rainfall characteristics are important to support hydrological and geomorphological studies. Experimentally, rainfall simulators are widely employed during research activities, both in the laboratory and in the field, to accomplish a wide range of research objectives and purposes. Rainfall simulators can be a useful tool to investigate, among many other applications, the relationship between rainfall and runoff, particularly focusing on water balances, , overland flow and associated transport processes, the rill and inter-rill erosion, and infiltration. They can help to predict the response of different land cover and soil types to precipitation and of sustainable semi-permeable solutions for implementation in the urban environment, to estimate the effect of land changes and deforestation on the land slope stability and sediment transport, to improve our knowledge on the transport of various pollutants associated with runoff, to investigate agricultural issues considering different levels of soil moisture and to calibrate precipitation gauges under controlled conditions.
In this session, research contributions addressing laboratory and in-situ experiments using rainfall simulators, in particular new developments and innovative techniques, as well as numerical simulations studies, are encouraged. Additional applications of rainfall simulators, if compared with those listed in the present proposal, are also welcome. This session provides a useful opportunity to collect an overview of rainfall simulators used worldwide, to identify their main common features that make results more comparable and breakthroughs in this field, and to exchange ideas to advance the field of simulated rainfall-based research in hydrology and geosciences.