Annual meeting of the HS9 subdivision for Erosion, Sedimentation and River Processes.

Meeting of the subdivision HS10 Ecohydrology, wetlands and estuaries. Exchange on the organization of the EGU General Assembly and general activities of the subdivision. Everybody interested is kindly invited.

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 for iPhone to an Arduino or Raspberri Pi? 3D printed an automated water quality sampler? Or build a Cloud Storage system from Open Source Components? Show it!

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

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

Water is our planet’s most vital resource, and the primary agent in some of the biggest hazards facing society and nature. The twin pressures of population growth and a rapidly changing global climate act as multipliers of water’s value and of water-related hazards.

River streamflow is one of the most crucial hydrological variables for ecology, for people and industry, for flood risk management and for understanding long term changes to the hydrological regime. However, despite significant efforts, long-term, spatially dense monitoring networks remain scarce, and even the best monitoring networks can fail to perform when faced with extreme conditions, and lack the precision and spatial coverage to fully represent crucial aspects of the hydrological cycle.

Happily, a number of new technologies and techniques are emerging which show great potential to meet these challenges. In this context, this session focuses on:
1) Innovative methodologies for measuring/modelling/estimating river stream flows;
2) Real-time acquisition of hydrological variables;
3) Remote sensing for hydrological & morphological monitoring;
4) Measuring extreme conditions associated with a changing climate;
5) Measurement of sudden-onset extreme flows associated with catastrophic events;
6) Strategies to quantify and describe hydro-morphological evolution of rivers;
7) New methods to cope with data-scarce environments;
8) Inter-comparison of innovative & classical models and approaches;
9) Evolution and refinement of existing methods;
10) Guidelines and standards for hydro-morphological streamflow monitoring;
11) Quantification of uncertainties;
12) Development of expert networks to advance methods.

Contributions are welcome with an emphasis on innovation, efficiency, operator safety, and meeting the growing challenges associated with the changing climate, and with natural and anthropogenically driven disasters such as dam failures and flash floods.

Additionally, presentations will be welcomed which explore options for greater collaboration in advancing riverflow methods and which link innovative research to operational monitoring.

This session is sponsored by the COST Action CA16219, Harmonisation of UAS techniques for agricultural and natural ecosystems monitoring (HARMONIOUS).

Within the water cycle, physical and chemical interactions between water, air and land shape the Earth’s surface. Human activity also induces major changes to natural systems at a wide range of temporal and spatial scales. Experimental methods have played – and still play – a fundamental role in Hydrology and Hydraulics. Laboratory- and field-based experiments allow physical systems to be analysed under semi-controlled conditions to understand process-form interactions. As such, experimental studies provide an effective platform for investigating physical processes under controlled hydrometeorological or physical conditions, and improve understanding of the Earth systems.

This session aims to provide with a discussion platform to exchange experiences on the design, methodologies and application of physical experiments in hydrology and hydraulics, both in the laboratory and the field. We welcome experimental research contributions across a series of disciplines with a hydrological, hydraulic and geomorphological focus across a wide range of spatiotemporal scales.

We invite contributions directing on (but not restricted to):
- The use of laboratory- and field-based experiments to understand real-world physical systems with a hydrological, geomorphological or hydraulic focus;
- Fundamental science and practical applications of physical and experimental models such as flumes, lysimeters, soil columns, rainfall simulators or scaled physical systems;
- The application of novel and innovative instrumentation, measurement and visualisation techniques;
- Experimental adaptations to well-established monitoring or data analysis techniques;
- Development and application of hybrid or composite (numerical-physical) models to contribute to numerical modelling frameworks;
- The use of experimental methods and models for science communication and as demonstrative teaching tools.

Geophysical and in-situ measurements of the cryosphere offer important baseline datasets, as well as validation for modelling and remote sensing products. In this session we welcome contributions related to a wide spectrum of methods, including, but not limited to radioglaciology, active and passive seismology, acoustic sounding, Global Navigation Satellite System (GNSS) reflectometry or time delay techniques, cosmic ray neutron sensing, remotely operated vehicle (ROV) or drone applications, geoelectrics, nuclear magnetic resonance (NMR) and methods in radiative transfer (i.e. infrared photography, thermal sounding...).

Contributions could be related to field applications, new approaches in geophysical or in-situ survey techniques, or theoretical advances in data analysis processing or inversion. Case studies from all parts of the cryosphere such as snow and firn, alpine glaciers, ice sheets, glacial and periglacial environments, permafrost, or sea ice, are highly welcome. The focus of the session is to compare experiences in the application, processing, analysis and interpretation of different geophysical and in-situ techniques in these highly complex environments.

This year our session will be a virtual PICO session. The session begins with each presenter giving a “quick fire” 2-minute overview of their research, followed by breakout "rooms" - one per presentation, for authors to further discuss their research. We hope the virtual PICO format will provide as much lively discussion as our normal in-person PICO!

++++++++++++++++++++ Invited Speaker ++++++++++++++++++++

Amy R. Macfarlane: Quasi in-situ snow and sea ice interface microstructure measured by micro-computed tomography

Recent advances in image collection, e.g. using uncrewed aerial vehicles (UAVs), and topographic measurements, e.g. using terrestrial or airborne LiDAR, are providing an unprecedented insight into landscape and process characterization in geosciences. In parallel, historical data including terrestrial, aerial, and satellite photos as well as historical digital elevation models (DEMs), can extend high-resolution time series and offer exciting potential to distinguish anthropogenic from natural causes of environmental change and to reconstruct the long-term evolution of the surface from local to landscape scale.

For both historic and contemporary scenarios, the rise of techniques with ‘structure from motion’ (SfM) processing has democratized data access and offers a new measurement paradigm to geoscientists. Photogrammetric and remote sensing data are now available on spatial scales from millimetres to kilometres and over durations of single events to lasting time series (e.g. from sub-second to decadal-duration time-lapse), allowing the evaluation of event magnitude and frequency interrelationships.

The session welcomes contributions from a broad range of geoscience disciplines such as geomorphology, cryosphere, volcanology, hydrology, bio-geosciences, and geology, addressing methodological and applied studies. Our goal is to create a diversified and interdisciplinary session to explore the potential, limitations, and challenges of topographic datasets for the reconstruction and interpretation of past and present 2D and 3D changes in different environments and processes. We further encourage contributions describing workflows that optimize data acquisition and processing to guarantee acceptable accuracies and to automate data application (e.g. geomorphic feature detection and tracking), and field-based experimental studies using novel multi-instrument and multi-scale methodologies. This session invites contributions on the state of the art and the latest developments in i) modern photogrammetric and topographic measurements, ii) remote sensing techniques as well as applications, iii) modelling technologies, and iv) data processing tools, for instance, using machine learning approaches.

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

The International Association of Hydrological Sciences (IAHS) coordinates two initiatives in hydrology:

- The Panta Rhei hydrological decade 2013- 2022, focusing on gains in our understanding of water cycle processes, their changing dynamics in respect of interactions and feedbacks with human systems. [1]
- The 23 Unsolved Problems in Hydrology (UPH), launched in 2017 after a public consultation process, in collaboration with the Hydrology Divisions of EGU and AGU as well as the IAH. [2]

This session presents works related to these initiatives.

Approaching the end of this Panta Rhei decade (2013-2022), it is time to synthesize the achievements of this decade. The main focus of this grand synthesis, which will be published in an IAHS book, is on coevolution and prediction of coupled human-water systems, including understanding of emergent phenomena, mechanisms, and implications for predictions and practices. Focus is put on theoretical/conceptual framework for understanding changes in hydrology and society; coevolution and emergent phenomena; dynamic models; data needs and acquisition; benchmark datasets in various context and scales, including human-flood, human-drought, agricultural, transboundary and global systems. Case studies from Panta Rhei working groups, IAHS Commissions and beyond are also welcome.

The 23 UPH are articulated around 7 themes: Time variability and change, Space variability and scaling, Variability of extremes, Interfaces in hydrology, Measurements and data, Modelling methods, and Interfaces with society. A crucial issue is to put together fragmented knowledge to address the questions raised and enhance coherence in hydrological sciences. The purpose of this session is to present research results that advance the understanding of any of the 23 UPH, review (or present a contribution to review) the state of the art of one (or more) of the UPH, pointing towards directions where progress is most promising.

[1] Panta-Rhei: https://iahs.info/Commissions--W-Groups/Working-Groups/Panta-Rhei.do
[2] 23 UPH: https://doi.org/10.1080/02626667.2019.1620507

Understanding the complex interactions of the coupled terrestrial-atmospheric water cycle requires cross-compartment strategies encompassing coupled modeling from the bedrock to the top of the atmosphere, integrated hydro-meteorological observations and datasets, novel data assimilation schemes and multivariable validation approaches. The objective of the session is to create opportunities for interdisciplinary exchange of ideas and experiences among members of the Earth System and hydrology communities. Contributions are invited dealing with the complex interactions between groundwater, surface water, land surface and atmospheric processes with a specific focus on the development, application and validation of novel one-way (both deterministic and ensemble) or fully-coupled hydrometeorological modeling systems for process understanding and predictions and projections across various space- and time scales. This includes also combined dynamical-statistical approaches and studies addressing data assimilation in coupled models. An additional focus is placed on the use of field experiments and testbeds equipped with complex sensors and measurement systems allowing cross-compartment and multivariable validation of these modeling systems.

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

The session further encourages discussion on interdisciplinary physical and data-based approaches to system dynamics in hydrology and broader geosciences, ranging from novel advances in stochastic, computational, information-theoretic and dynamical system analysis, to cross-cutting emerging pathways in information physics.

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

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

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

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

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

We are glad to welcome Mahesh Maskey (dynamical systems) and Uwe Ehret (information theory) as our invited authors for this eclectic session, where we promote a fruitful cross-fertilisation between complementary visions of the world.

In recent years, the geoscience community has been making strides towards making our science more open, inclusive, and accessible, driven both by individual- or community-led initiatives and by broader-scale regulatory changes. Open-source software, accessible codebases and open online collaboration resources (such as GitHub, VHub, etc.) are becoming the norm in many disciplines. The open-access publishing landscape has been changing too: several geoscience journals have defined data availability policies, and many publishers have introduced green and gold open-access options to their journal collections. Pre-print servers and grassroots diamond open-access journals are changing the readiness with which scholarly content can be accessed beyond the traditional paywall model.

However, good scientific practice requires research results to be reproducible, experiments to be repeatable and methods to be reusable. This can be a challenge in geosciences, with available data sets that are becoming more complex and constantly superseded by new, improved releases. Similarly, new models and computational tools keep emerging in different versions and programming languages, with a large variability in the quality of the documentation. Moreover, how data and models are linked together towards scientific output is very rarely documented in a reproducible way. As a result, very few published results are reproducible for the general reader. These challenges especially apply to hydrology, which is highlighted here as an example in the general geosciences.

This session is designed to gain a community overview of the current open-science landscape and how this is expected to evolve in the future. It aims to foster a debate on open science, lower the bar for engaging in open science and showcase examples, including software and other instruments for assisting open research. This may include software and tools, open science dissemination platforms (such as pre-print servers and journals), the teams driving the development of open-science resources and practices, and discussion on the regulatory moves towards standardising open access in the scientific community and what those policies mean in practice. The session has a focus on hydrological sciences, as an example within the geosciences. This session should advance the discussion on open and reproducible science, highlight its advantages and also provide the means to bring this into practice.

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

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

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

Annually, various parts of Africa are affected by climate related impacts, such as droughts, flooding etc., to varying degrees of severity. Global and regional hydrological models have recently seen tremendous advances in improved representations of physical processes underpinning these impacts, resulting in better reproductions of observed variables such as streamflow and water extent. As a result, they are increasingly used for predicting socio-economic risks of floods, droughts and water stress in regions around the globe. However, the use of hydroclimatic models for disaster risk reductions in data-sparse regions, while gradually improving, is still limited in comparison.
This session aims to bring together communities working on different strands of African hydrology, climate and other water-related topics, including environmental and food security. We welcome both fundamental and applied research in the areas of hydrological process understanding, flood forecasting and mapping, seasonal forecasting, water resources management, climate impact assessment and societal impacts. Interdisciplinary studies aiming at increasing our understanding of the physical drivers of water-related risks and their impacts in Africa are encouraged. Case studies showcasing practical experiments and innovative solutions in decision making under large uncertainty are welcomed.

A large proportion of the global stream network comprises channels that cease to flow or dry periodically. These systems range from near-perennial rivers with infrequent, short periods of zero flow to rivers experiencing flow only episodically following large rainfall events. Intermittent and ephemeral rivers support a unique high-biodiversity because they are coupled aquatic-terrestrial systems that accommodate a wide range of aquatic, semi-aquatic and terrestrial flora and fauna. Extension and connection of the flowing stream network can affect the quantity and quality of water in downstream perennial rivers. In many arid conditions, they are the main source of fresh water for consumptive use. However, in many places intermittent and ephemeral rivers lack protection and adequate management. There is a clear need to study the hydrology, ecology and biogeochemistry of natural intermittent and ephemeral streams to characterize their flow regimes, to understand the main origins of flow intermittence and how this affects their biodiversity, and to assess the consequences of altered flow intermittency (both increased and decreased) in river systems.
This session welcomes all contributions on the science and management of intermittent and ephemeral streams, and particularly those illustrating:
• current advances and approaches in characterizing and modelling flow intermittency,
• the effects of flow in intermittent streams on downstream perennial streams,
• the factors that affect flowing stream network dynamics
• land use and climate change impacts on flow intermittency,
• links between flow intermittency and biogeochemistry and/or ecology.

Agriculture plays a vital role in the socio-economic development. For agricultural production, whether rainfed or using irrigation, water is a key requirement. Therefore, a thorough understanding of the hydrological processes in agricultural lands is essential to address a wide range of issues, including soil moisture condition, crop water requirement, agricultural productivity, water efficiency, soil erosion, and solute transport.
This session is intended to address and advance our understanding of the role of hydrological processes in agricultural lands. Some of the topics and questions of interest are: (1) modelling the impacts of climate change on water balance and agricultural productivity at watershed scale; (2) identification of dominant hydrological factors and how they can be measured locally for improving water supply to crops; (3) effects of irrigation schemes on regional evapotranspiration and soil moisture content; (4) effects of artificial drainage on water regime and solute transport at different spatial scales; (5) aquifer vulnerability to high rates of fertilizer and pesticide applications; (6) multi-process and multi-scale water and energy transitions in agricultural lands; (7) water and energy responses of water-saving practice; and (8) linking hydrological issues with other environmental issues, including removal of natural vegetation, drought or flood events, and soil erosion. We welcome abstracts addressing the above topics or other topics related to hydrological processes in agricultural lands.

Forests are recognized as prime regulators of the hydrological cycle. Their change has effects on the ecosystem services they provide via their water and biochemical cycles. The traditional idea that forest hydrology emphasizes the role of forests and forest management practices on runoff generation and water quality has been broadened in the light of rapid global change. Some of the largest pristine forested areas are in the tropics and have suffered drastic land-use changes during recent decades. These tropical systems are still markedly underrepresented in hydrological studies compared to temperate regions, especially concerning long-term experimental setups and monitoring networks.
Anthropogenic intervention is exerting enormous pressure on natural ecosystems, affecting water quantity and quality, and, consequently, threatening socio-economic and human development as described by the UN Sustainable Development Goals. Yet, we lack a proper understanding of how catchments respond to changing environmental conditions and disturbances. To answer these open questions, it requires interdisciplinary approaches in combination with novel monitoring methods and modelling efforts. This session brings together studies that will enhance our understanding and stimulate discussions on the impact of global change on hydrological processes in forest systems at different scales.
We invite field experimentalists and modelers to submit contributions that investigate hydrological processes in forests from boreal to tropical regions, including water quality, the carbon cycle, or ecohydrological aspects.
This session welcomes studies that:
1) Improves our understanding of forested hydrological processes using an experimental or modelling approach or a combination of both;
2) Assesses the hydrological-related impacts of land use/cover change in forested systems;
3) Presents new methods (e.g. remote sensing techniques) or tools that unveils new perspectives or data sources in forest hydrology;
4) Includes interdisciplinary research that supports the consideration of overlooked soil-plant-atmosphere components in hydrological studies.

Despite only representing about 25% of continental land, mountains are an essential part of the global ecosystem and are recognised to be the source of much of the world’s surfaces water supply apart from important sources of other commodities like energy, minerals, forest, and agricultural products, and recreation areas. In addition, mountains represent a storehouse for biodiversity and ecosystem services. People residing within mountains or in their foothills represent approximately 26% of the world’s population, and this percentage increases to nearly 40% when considering those who live within watersheds of rivers originated in a mountain range. This makes mountains particularly sensitive to climate variability, but also unique areas for identifying and monitoring the effects of global change thanks to the rapid dynamics of their physical and biological systems.
This session aims to bring together the scientific community doing hydrology research on mountain ranges across the globe to share results and experiences. Therefore, this session invites contributions addressing past, present, and future changes in mountain hydrology due to changes in either climate and/or land use, how these changes affect local and downstream territories, and adaptation strategies to ensure the long-term sustainability of mountain ecosystem services, with a special focus on water cycle regulation and water resources generation. Example topics of interest for this session are:
• Sources of information for evaluating past and present conditions (in either surface and/or groundwater systems).
• Methods for differentiating climatic and anthropogenic drivers of hydrological change.
• Modelling approaches to assess hydrological change.
• Evolution, forecasting, and impacts of extreme events.
• Case studies on adaptation to changing water resources availability.

By accumulating precipitation at high elevations, snow and ice change the hydrologic response of a watershed. Water stored in the snow pack and in glaciers thus represents an important component of the hydrological budget in many regions of the world and a sustainment to life during dry seasons. Predicted impacts of climate change in headwater catchments (including a shift from snow to rain, earlier snowmelt and a decrease in peak snow accumulation) will affect both water resources distribution and water uses at multiple scales, with potential implications for energy and food production.
Our knowledge about snow/ice accumulation and melt patterns is highly uncertain, because of both limited availability and inherently large spatial variability of hydrological and weather data in remote areas at high elevations. This translates into limited process understanding, especially in a warming climate. The objective of this session is to integrate specialists focusing on snow accumulation and melt within the context of catchment hydrology and snow as a source for glacier ice and melt, hence streamflow. The aim is to integrate and share knowledge and experiences about experimental research, remote sensing and modelling.
Contributions addressing the following topics are welcome:
- experimental research on snowmelt 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 (time-lapse imagery, laser scanners, radar, optical photography, thermal and hyperspectral technologies) or in-situ snow products (albedo, snow cover or depth, snow water equivalent) 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 dynamic or the application of techniques for tracing water flow paths;
- studies on cryosphere-influenced mountain hydrology, such as landforms at high elevation and their relationship with streamflow, water balance of snow/ice-dominated, mountain regions.

Snow cover characteristics (e.g. spatial distribution, surface and internal physical properties) are continuously evolving over a wide range of scales due to meteorological conditions, such as precipitation, wind and radiation.
Most processes occurring in the snow cover depend on the vertical and horizontal distribution of its physical properties, which are primarily controlled by the microstructure of snow (e.g. density, specific surface area). In turn, snow metamorphism changes the microstructure, leading to feedback loops that affect the snow cover on coarser scales. This can have far-reaching implications for a wide range of applications, including snow hydrology, weather forecasting, climate modelling, and avalanche hazard forecasting or remote sensing of snow. The characterization of snow thus demands synergetic investigations of the hierarchy of processes across the scales ranging from explicit microstructure-based studies to sub-grid parameterizations for unresolved processes in large-scale phenomena (e.g. albedo, drifting snow).

This session is therefore devoted to modelling and measuring snow processes across scales. The aim is to gather researchers from various disciplines to share their expertise on snow processes in seasonal and perennial snowpacks. We invite contributions ranging from “small” scales, as encountered in microstructure studies, over “intermediate” scales typically relevant for 1D snowpack models, up to “coarse” scales, that typically emerge for spatially distributed modelling over mountainous or polar snow- and ice-covered terrain. Specifically, we welcome contributions reporting results from field, laboratory and numerical studies of the physical and chemical evolution of snowpacks, statistical or dynamic downscaling methods of atmospheric driving data, assimilation of in-situ and remotely sensed observations, representation of sub-grid processes in coarse-scale models, and evaluation of model performance and associated uncertainties.

Understanding and representing hydrological processes is the basis for developing and improving hydrological and Earth system models. Modeling and learning is a symbiotic and continuous process through which our understanding of human-natural systems is formulated and tested constantly. As a result, a variety of models are developed and trained by quantitative and qualitative data across desired temporal and spatial scales.
In this session, we welcome contributions on the development of novel data sets and frameworks for model development and evaluation across spatio-temporal scales from catchment to continental scale hydrology. The vision of our session, following the initiative of 23 Unsolved Problems in Hydrology (UPH, https://doi.org/10.1080/02626667.2019.1620507), is to address three questions: What are the hydrologic laws at the catchment scale and how do they change with scale? How can hydrological models be adapted to be able to extrapolate to changing conditions, including changing vegetation dynamics? How can we disentangle and reduce model structural/parameter/input uncertainty in hydrological prediction?

We welcome contributions that (but not limited to):
(1) introduce new global and regional data products into the modeling process;
(2) introduce new approaches for model calibration and evaluation, especially to improve process representation, and/or to improve model predictions under changing conditions;
(3) improve model structure by representing often neglected processes in hydrological models such as human impacts, river regulations, irrigation, as well as vegetation dynamics;
(4) provide novel concepts for improving the characterization of internal and external model fluxes and their spatio-temporal dynamics;
(5) upscale experimentalists' knowledge from smaller to larger scale by identifying driving forces for spatial patterns for a better usage of them in models;
(6) suggest more effective monitoring and seamless modeling of spatial patterns in hydrology and land models using distributed earth observations;
(7) develop novel approaches and performance metrics for evaluating and constraining models in space and time; and
(8) identify model limitations and conceptual improvements that are of general relevance to the geosciences modeling community.

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

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

Salinisation of both groundwater and surface water resources is a growing problem, threatening freshwater security for agricultural, domestic and industrial purposes, as well as biodiversity, in many regions of the world. Although the problem of freshwater salinisation is increasingly recognised, there are major research gaps in terms of its impacts, extent and magnitude, particularly at cross-regional to global scales. Both observational, remote sensing and model-driven approaches are needed to improve our understanding of salinisation processes, drivers and impacts across different scales, and to ensure sustainable water resources management today and in the future.

This session aims to bring together scientists working on salinity monitoring (in-situ or remote sensing) data, as well as model-driven studies related to quantifying and predicting historic to future salinisation patterns, drivers and impacts at catchment to global scales. Contributions including - but not limited to - any of the following topics are of particular interest for this session:

- Surface water and groundwater interactions and its effects on salinity dynamics
- Impacts of hydrological extremes and seasonality on salinity levels of freshwater resources
- Human and hydro-climatic drivers of freshwater salinisation across different spatial and temporal scales
- Implications of inland salinity for ecosystem health and sectoral water use
- Applications of surface and/or groundwater in-situ and remote sensing data, and/or data-driven models to determine salinity concentrations across multiple scales
- Global change (e.g. climate change, land use change) impacts on future freshwater salinisation
- Assessment of management and adaptation measures to salinity changes

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

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

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

Surface water quality is typically assessed and managed at the catchment scale. Management decisions needs a sound process knowledge and understanding of underlying cause-effect relationships to be effective. However, the dynamics of solute and particulate concentrations integrate a multitude of hydrological and biogeochemical processes interacting at different temporal and spatial scales, which are difficult to assess using local field experiments. Hence, time series of water quality observed at the outlet of catchments can be highly beneficial to understand these processes. Long-term, high-frequency as well as multiple-site datasets can be used to inform experimental and modelling studies and formulate hypotheses on dominant ecohydrological and geochemical processes moving “from pattern to process”. Recent advances in this field have used concentration-discharge relationships to infer the interplay between hydrological and biogeochemical controls, both in the terrestrial part of catchments and in the river network. Long-term time series of nutrient input-output relationships help understand nutrients legacy effects and catchments response times. High-frequency observations allow understanding the fine structure of concentration dynamics, including flowpaths and their age distribution during runoff events and ecological controls on diel cycles. When multiple catchments are monitored, it is possible to relate water quality metrics to catchment properties to conclude on dominant processes.
This session aims to bring together studies using data-driven analysis of river concentration time series to infer solute and particulate mobilization, retention and export mechanisms. We strongly encourage studies that use findings from data-driven analysis to build conceptual and process-based models. Presentations of the following topics are invited:
- Interpretation of C-Q relationships from storm events to long-term shifts
- Utilization of high-frequency observations of water quality
- Long-term changes of nutrient inputs, outputs and nutrient stoichiometry
- Role of hydrological extremes such as the recent mid-European droughts in long-term trajectories of nutrient exports
- Instream, network and lake effects on nutrient load and concentration dynamics
- Utilizing time series of compound-specific isotopic fingerprints
- Linkage of water travel time distribution and water quality dynamics

A large number of pathogens, micropollutants and their transformation products (veterinary and human pharmaceuticals, personal care products, pesticides and biocides, chlorinated compounds, heavy metals) pose a risk for soil, groundwater and surface water. The large diversity of compounds and of their sources makes the quantification of their occurrence in the terrestrial and aquatic environment across space and time a challenging task. Regulatory monitoring programmes cover a small selection out of the compound diversity and quantify these selected compounds only at coarse temporal and spatial resolution. Carefully designed monitoring however allows to detect and elucidate processes and to estimate parameters in the aquatic environment. Modeling is a complementary tool to generalize measured data and extrapolate in time and space, which is needed as a basis for scenario analysis and decision making.

This session invites contributions that improve our quantitative understanding of the sources and pathways, mass fluxes, the fate and transport of micropollutants and pathogens in the soil-groundwater-river continuum. Topics cover:
- Novel sampling and monitoring concepts and devices
- New analytical methods, new detection methods for DNA, pathogens, micropollutants, non-target screening
- Experimental studies and modelling approaches to quantify diffuse and point source inputs
- Novel monitoring approaches such as non-target screening as tools for improving processes understanding and source identification such as industries
- Comparative fate studies on parent compounds and transformation products
- Diffuse sources and (re-)emerging chemicals
- Biogeochemical interactions and impact on micropollutant behaviour

Plastic pollution in freshwater systems is a widely recognized global problem with potential environmental risks to water and sediment quality. Furthermore, freshwater plastic pollution is also considered the dominant source of plastic input to the oceans. Despite this, research on plastic pollution has only recently expanded from the marine environment to freshwater systems. Therefore data and knowledge from field studies are still limited in regard to freshwater environments. Sources, quantities, distribution across environmental matrices and ecosystem compartments, and transport mechanisms remain mostly unknown at catchment scale. These knowledge gaps must be addressed to understand the dispersal and eventual fate of plastics in the environment, enabling a better assessment of potential risks as well as development of effective mitigation measures.
In this session, we explore the current state of knowledge and activities on macro-, micro- and nanoplastics in freshwater systems, including aspects such as:
• Plastics in rivers, lakes, urban water systems, floodplains, estuaries, freshwater biota;
• Monitoring and analysis techniques;
• Source to sink investigations, considering quantities and distribution across environmental matrices (water and sediment) and compartments (water surface layer, water column, ice, riverbed, and riverbanks);
• Transport processes of plastics at catchment scale;
• The role of river regulation structures, e.g. dams, navigation, flood control, etc., in plastic retention and transport
• Effects of hydrological extremes, e.g. accumulation of plastics during droughts, and short-term export during floods in the catchment;
• Degradation and fragmentation processes, e.g. from macro- to micro- and nanoplastics;
• Modelling approaches for local and/or global river output estimations;
• Legislative/regulatory efforts, such as monitoring programs and measures against plastic pollution in freshwater systems.

(Contributions with a strong focus on remote sensing of plastics are encouraged to be submitted to the session “Detecting and Monitoring Plastic Pollution in Rivers, Lakes, and Oceans”)

This session presents the works submitted to session HS2.3.5 “Fate and transport processes of pathogens and emerging contaminants at multiple scales” and to session HS6.9 “From short-term detection to long-term projections: complementing water quality assessments by combining modelling and remote sensing”.
HS2.3.5 Invited speaker: Dr. Liping Pang, ESR Christchurch, NZ
The occurrence of pathogens and an exponentially increasing number of contaminants in freshwater and estuary environments pose a serious problem to public health. There is a need to better understand the dominant processes controlling fecal indicator, pathogen and contaminant fate and transport at larger scales. Consequently, we welcome contributions that include both small and large-scale experimental and modelling studies with a focus on:
- The development of novel experimental and analytical methods to investigate fate and transport of fecal indicators, pathogens and emerging contaminants in rivers, groundwater and estuaries
- Hydrological, physically based modelling approaches
- Methods for identifying the dominant processes and for transferring fecal indicator, pathogen and contaminant transport parameters from the laboratory to the field or catchment scale
- Investigations of the implications of contamination of water resources for water safety management planning and risk assessment frameworks

HS6.9
Climate change and major socio-economic developments such as increasing population and expanding public water supplies that fail to adequately treat wastewater flows lead to significant water quality deterioration. An exponentially increasing number of contaminants and nutrients in freshwater and estuary environments pose a serious problem to public and ecosystem health. This part of the session focuses on regional and global water quality research where remote sensing and modelling are combined in order to complement a water quality assessment compared to one based on monitoring data only. Topics of interest:

- Remote sensing facilitating water quality model development and modelling
- Processing water quality data from remote sensing products across scales
- Improve water quality assessments

Our invited speaker is Lucy Marshall from the University of New South Wales, Sydney, Australia.

The application of multi-datasets and multi-objective functions has proven to improve the performance of hydrologic and water quality models by extracting complementary information from multiple data sources or multiple features of modelled variables. This is useful if more than one variable (runoff and snow cover, sediment or pollutant concentration) or more than one characteristic of the same variable (e.g., flood peaks and recession curves) are of interest.
Similarly, a multi-model approach can overcome shortcomings of individual models, while testing a model at multiple scales helps to improve our understanding of the model functioning in relation to catchment processes. Finally, the quantification of multiple uncertainty sources enables the identification of their individual contributions and this is critical for uncertainty reduction and decision making under uncertainty. In this aspect, Bayesian approaches emerge as very powerful tools for comprehensive handling of uncertainty in data, model structure and parameters.

This session welcomes contributions that apply one or more of the multi-aspects in hydrologic and water quality studies. In particular, we seek studies covering the following issues:
• Frameworks using multi-objectives or multi-variables to improve the identification (prediction) of hydrologic or water quality models
• Studies using multi-model or multiple-data-driven approaches
• Use of multiple scales or sites to improve understanding of catchment processes
• Assimilation of remote sensed data or use of multi-datasets to improve model identification
• Hypothesis testing with one of the multi-aspects
• Metaheuristics (e.g., Monte Carlo) or Bayesian approaches in combination with multi-aspects of model identification
• Techniques to optimize model calibration or uncertainty quantification via multi-aspect analyses
• Studies handling multiple uncertainty sources in a modelling framework
• Bayesian applications to address the problem of scaling (e.g. disparity between process, observations, model resolution and predictions) through hierarchical models
• Bayesian approaches to model water quality in data sparse environments
• Applications of Bayesian Belief Networks as decision support tools
• Application of machine learning and data mining approaches to learn from large, multiple or high-resolution data sets.

Estimates of water availability and flooding risks remain one of the central scientific and societal challenges of the 21st century. The complexity of this challenge arises particularly from transient boundary conditions: Increasing atmospheric greenhouse gas concentrations lead to global warming and an intensification of the water cycle and finally to shifts in the temporal and spatial distribution of precipitation and terrestrial water availability. Likewise, large-scale land use changes impact and alter regional atmospheric circulation, thereby local precipitation characteristics and again terrestrial water availability. Also the feedbacks between the interlinked terrestrial and atmospheric processes on different spatial and temporal scales are still poorly understood.
This session therefore invites contributions addressing past, present and prospective changes in regional hydrological behaviour due to either (or joint) climate- and/or land use changes. We especially welcome contributions on the development of novel methods and methodologies to quantify hydrological change. Further aspects of this topic comprise particularly:

- Robustness of hydrological impact assessments based on scenarios using downscaled climate model – hydrology model modelling chains.
- Quantification of regional land use change predictions and impact of past, present and future land use changes on water and energy fluxes in meso- to large-scale catchments.
- Joint or coupled modelling of water and energy fluxes between the atmosphere and the land surface/subsurface and analyses of feedback mechanisms.
- Climate change/land use change signal separation techniques and quantification of future land use change vs. climate change induced hydrological change.
- Adequate handling of climate change and land use change data and their uncertainty for the forcing of hydrological models.
- Case studies of regional hydrological behaviour in climate sensitive and flood or drought prone regions worldwide.

In the current context of global change, assessing the impact of climate variability and changes on hydrological systems and water resources is increasingly crucial for society to better-adapt to future shifts in water resources as well as extreme conditions (floods and droughts). However, hitherto, important sources of uncertainties have often been neglected in projecting climate impacts on hydrological systems, especially uncertainties associated with internal/natural climate variability, whose contribution to near-future changes could be as important as forced anthropogenic climate changes at the regional scales. Internal climate modes of variability (e.g. ENSO, NAO, AMO) and their impact on the continent are not always properly reproduced in the current global climate models, leading to large underestimations of decadal climate and hydroclimatic variability at the global scale. At the same time, hydrological response strongly depends on catchment properties, whose interactions with climate variability are little understood at the decadal timescales. These factors altogether reduce significantly our ability to understand long-term hydrological variability and to improve projection and reconstruction of future and past hydrological changes on which improvement of adaption scenarios depends.

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

Hydrological extremes (floods and droughts) have major impacts on society and ecosystems and are expected to increase in frequency and severity with climate change. Although both at the extreme ends of the hydrological spectrum, floods and droughts are governed by different processes, which means that they operate on different spatial and temporal scales and that different approaches and indices are needed to characterise them. However, there are also many similarities and links between the two extremes that are increasingly being studied.

This session on hydrological extremes aims to bring together the two communities in order to learn from the similarities and differences between flood and drought research. We aim to increase the understanding of the governing processes of both hydrological extremes, find robust ways of modelling and analysing floods and droughts, assess the influence of global change on hydroclimatic extremes, and study the socio-economic and environmental impacts of both extremes.

We welcome submissions that present innovative flood and/or drought research, including insightful case studies, large-sample studies, statistical hydrology, and analysis of flood or drought nonstationarity under the effects of climate change, land cover change, and other anthropogenic influences.

This session is jointly organised by the Panta Rhei Working Groups “Understanding Flood Changes”, “Changes in Flood Risk”, and “Drought in the Anthropocene” and will further stimulate scientific discussion on change detection, attribution, and the feedbacks between hydrological extremes and society. The session is linked to the European Low Flow and Drought Group of UNESCO´s IHP-VIII FRIEND-Water Program, which aims to promote international drought research. Submissions from early-career researchers are especially encouraged.

Key topics:
Floods, Droughts, or both
Hydrological extremes
Large-sample hydrology or insightful case studies
Flood and drought nonstationarity
New approaches for analysis of extremes
Spatial and temporal variability

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

Flash droughts (FDs) are distinguished from slower-developing droughts by their rapid rate of intensification. They may occur during the initial stage of a long-term drought, represent a period of rapid intensification within a longer-term drought, or terminate after a relatively short, yet impactful, event. Due to their rapid development, FDs are difficult to manage and can be particularly devastating for agriculture. They can occur with little or no warning due to limitations in monitoring capabilities, prediction skill of relevant environmental variables, and understanding of key physical mechanisms. Efforts to create working definitions of FD have been hindered by these limitations and a lack of data to quantify the many impacts associated with FD. This session welcomes abstracts relating to:
1) proposed FD definitions,
2) regionality and seasonality of FD physical mechanisms,
3) advances in FD detection and monitoring,
4) predictability and prediction of FDs,
5) quantification of impacts of FD, and
6) the changes in FD frequency and intensity in response to human-induced climate change.
We also encourage contributions that benefit from multivariate analysis, model-observation comparison, uncertainty quantification, or machine-learning predictions.

With global climate change affecting the frequency and severity of extreme meteorological and hydrological events, it is particularly necessary to develop models and methodologies for a better understanding and forecasting of present day weather induced hazards. Future changes in the event characteristics as well as changes in vulnerability and exposure are among the further factors for determining risks for infrastructure and society, and for the development of suitable adaptation measures. This session considers extreme events that lead to disastrous hazards induced by severe weather and climate change. These can, e.g., be tropical or extratropical rain- and wind-storms, hail, tornadoes or lightning events, but also floods, long-lasting periods of drought, periods of extremely high or of extremely low temperatures, etc. Papers are sought which contribute to the understanding of their occurrence (conditions and meteorological development), to assessment of their risk and their future changes, to the ability of models to reproduce them and methods to forecast them or produce early warnings, to proactive planning focusing to damage prevention and damage reduction. Papers are also encouraged that look at complex extreme events produced by combinations or sequences of factors that are not extreme by themselves. The session serves as a forum for the interdisciplinary exchange of research approaches and results, involving meteorology, hydrology, hazard management and applications like insurance issues.

Global, continental, and other large-scale hydrological research is very important in many different contexts. Examples include; increasing understanding of the climate system and water cycle, assessment of water resources in a changing environment, hydrological forecasting, and water resource management.

We invite contributions from across the atmospheric, meteorological and hydrological communities. In particular, we welcome abstracts that address advances in:

(i) understanding and predicting the current and future state of our global and large scale water resources;

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

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

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

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

Since early work on the assessment of global, continental and regional-scale water balance components, many studies use different approaches including global models, as well as data-driven approaches that ingest in-situ or remotely sensed observations or combination of these. They attempted to quantify water fluxes (e.g. evapotranspiration, runoff/discharge, groundwater recharge) and water storages 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, more and more 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 calculations differ considerably due to the methodology and datasets used such that a robust assessment of global, continental and regional water balance components is challenging.
This session is seeking for contributions that are focusing on the:
i. past/future assessment of water balance components (fluxes and storages) such as precipitation, river discharge 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.

Large-sample studies lead to generalizable insights about hydrologic similarity, understanding of dominant hydrologic processes and modelling capabilities. Studies that investigate the organization and response of single catchments (e.g. well-monitored experimental catchments, innovative process models) can provide a testing ground for hydrologic theories that can scaled up to larger samples. Combining detailed local knowledge with large data samples can provide insights unavailable to either approach alone, about e.g. hydrologic organization across large spatial scales or across varied hydroclimatic conditions.

This session provides the opportunity for researchers to highlight recent data and model-based efforts on catchment organization, diversity and response. We specifically encourage studies that seek to advance understanding of the following topics:

1. Data mobilization for hydrologic similarity and regionalization:
Can currently available global datasets of hydrologically relevant information (e.g. soil properties, land use, soil moisture estimates, meteorological re-analysis) effectively be used to define hydrologic similarity and thus improve the prediction in ungauged or scarcely gauged basins?

2. Testing of hydrologic theories:
To what extent can hydrologic theory developed in well-monitored experimental catchments be transferred to larger samples of relatively data-scarce catchments?

3. Modelling capabilities:
What can large sample hydrology reveal about the strengths and weaknesses of current modelling capabilities and how can large sample approaches be used to improve and constrain modelling efforts?

4. Explaining water use dynamics:
How can we use large sample hydrology to better understand water resource use, allocation and future availability, and inform sustainable management of these resources?

5. Development and improvement of large-sample data sets:
How can we overcome current challenges on unequal geographical representation of catchments, quantification of uncertainty, catchment heterogeneity and inclusion of human interaction with the global water cycle?

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

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

Reducing natural hazard risk is high on the global political agenda. In response, more and more risk datasets, methods, and models are being developed and applied together with stakeholders in the decision-making process. At the same time, climate change, globalisation, urbanisation, and increased interconnectedness between ecological, physical, human, and technological systems pose major challenges to disaster risk reduction in a globally interconnected world. COVID-19 has clearly shown that single-hazard approaches to disaster risk management can leave countries unprepared. This calls for novel scientific approaches and new types of data, including loss data, to integrate the study of multiple natural and human processes. The integration of socioeconomic loss databases in risk assessments allows for effective use for both science and policy. This session is a merger between the following sessions:

Global and continental scale risk assessment for natural hazards: methods, practice and open loss and risk assessment
In this sub-session we: (1) showcase current state-of-the-art in global and continental natural hazard risk science, assessment, and application; (2) foster exchange of knowledge and good practice between scientists and practitioners; and (3) collaboratively identify future research avenues. We examine all aspects of natural hazard risk assessment at the continental to global scale, including contributions focusing on single hazards, multiple hazards, or a combination or cascade of hazards. It includes contributions focusing on globally applicable methods, such as using globally available datasets to force more local models or inform more local risk assessment.

Interplay between natural hazards and vulnerable societies in the context of global change
This sub-session aims to: (1) gather research, empirical studies, and observation data that are useful for understanding and assessing risk to inform resilience building strategies in the context of global change, (2) identify persistent gaps, and (3) propose potential ways forward. The session welcomes contributions on the following topics, among others: What can we learn from comparative studies of past successes and failures? Why do we still see increasing impacts of natural hazards despite major progress in understanding their drivers and constant innovation in methods? Which approaches are needed to assess and manage multi-hazard and multi-risk?

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

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

* Predictive and analytical models based on the methods of statistics, computational intelligence, machine learning : neural networks (including deep learning), fuzzy systems, genetic programming, cellular automata, chaos theory, etc.
* Innovative sensing techniques: satellites, gauges and citizens (crowdsourcing)
* Methods for the analysis of complex data sets, including remote sensing data: principal and independent component analysis, time series analysis, information theory, etc.
* Specific concepts and methods of Big Data and Data Science
* Optimisation methods associated with heuristic search procedures: various types of evolutionary algorithms, randomised and adaptive search, etc.
* Applications of systems analysis and optimisation in water resources
* Hybrid modelling involving different types of models both process-based and data-driven, combination of models (multi-models), etc.
* Data assimilation and model reduction in integrated modelling
* Novel methods of analysing model uncertainty and sensitivity
* Software architectures for linking different types of models and data sources

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

Geostatistical methods are commonly applied in the Water, Earth and Environmental sciences to quantify spatial variation, produce interpolated maps with quantified uncertainty and optimize spatial sampling designs. Space-time geostatistics explores the dynamic aspects of environmental processes and characterise the dynamic variation in terms of correlations. Geostatistics can also be combined with machine learning and mechanistic models to improve the modelling of real-world processes and patterns. Such methods are used to model soil properties, produce climate model outputs, simulate hydrological processes, and to better understand and predict uncertainties overall. Big data analysis and data fusion have become major topics of research due to technological advances and the abundance of new data sources from remote and proximal sensing as well as a multitude of environmental sensor networks. Methodological advances, such as hierarchical Bayesian modeling, machine learning, sparse Gaussian processes, local interaction models, as well as advances in geostatistical software modules in R and Python have enhanced the geostatistical toolbox.

This session aims to provide a forum where scientists from different disciplines can present and discuss innovative geostatistical methods targeting important problems in the Water, Earth and Environmental sciences. We also encourage contributions focusing on real-world applications of state-of-the-art geostatistical methods.

The topics of interest include:
1) Space-time geostatistics for hydrology, soil, climate system observations and modelling
2) Hybrid methods: Integration of geostatistics with optimization and machine learning approaches
3) Advanced parametric and non-parametric spatial estimation and prediction techniques
4) Big spatial data: analysis and visualization
5) Optimisation of spatial sampling frameworks and space-time monitoring designs
6) Algorithms and applications on Earth Observation Systems
7) Data Fusion, mining and information analysis
8) Geostatistical characterization of uncertainties and error propagation
9) Bayesian geostatistical analysis and hierarchical modelling
10) Functional data analysis approaches to geostatistics
11) Multiple point geostatistics

This session is co-sponsored by the International Association for Mathematical Geosciences (IAMG), https://www.iamg.org/

Machine learning (ML) is now widely used across Hydrology and the broader Earth Sciences and especially its subfield deep learning (DL) has recently enjoyed increased attention.. This session highlights the continued integration of ML, and its many variants, including deep learning (DL), into traditional and emerging Hydrology-related workflows. Abstracts are solicited related to novel theory development, novel methodology, or practical applications of ML and DL in hydrological modeling. This might include, but is not limited to, the following:

(1) Development of novel DL models or modeling workflows.
(2) Integrating DL with process-based models and/or physical understanding.
(3) Improving understanding of the (internal) states/representations of ML/DL models.
(4) Understanding the reliability of ML/DL, including under nonstationarity.
(5) Deriving scaling relationships or process-related insights with ML/DL.
(6) Modeling human behavior and impacts on the hydrological cycle.
(7) Hazard analysis, detection, and mitigation.
(8) Natural Language Processing in support of models and/or modeling workflows

Clustering analysis is a well-known exploratory task for partitioning databases into smaller groups based on patterns or inherent similarity in data. Clustering methods have found many applications in many disciplines due to growing interest in unravelling the hidden and meaningful patterns that exist in large amounts of available data. Due to its unsupervised nature, clustering data is a complex task that requires attention to optimal choice alternatives regarding methods, model parameters and performance metrics. However, the suitability of clustering algorithms depends on their application. Different methods and approaches co-exist in a large pool. The challenge is to obtain application-specific insights while enabling a practical knowledge perspective for benchmarking. There are still research gaps in the wider clustering literature, and hydrology-specific knowledge is fragmented and difficult to find.

In hydrology, unsupervised classification of multivariate data is often used but typically in rather basic forms and as an intermediate step. Recently, the number of studies using clustering methods has rapidly increased. However, a clear and integrative vision on clustering algorithms is currently missing. Despite advances in other fields, the scope of hydrological studies is limited. Knowledge exchange on hydrology-specific ways of dealing with the issues related to clustering is needed.

The aim of this session is to explore theoretical and conceptual underpinnings of well-known clustering methods, offer fresh insights into applications of new clustering methods, gain thorough understanding of pearls and pitfalls in clustering algorithms, provide a critical overview of the main challenges associated with data clustering process, discuss major research trends and highlight open research issues. It is expected to improve scientific practice within the hydrology domain, and foster scientific debate on benchmarking in cluster analysis.

We invite contributions (case studies, comparative analyses, theoretical experiments) on a wide range of topics including (but not limited to): hard vs fuzzy clustering; comparison of clustering algorithms; benchmarking in cluster analysis; clustering as an exploratory tool vs clustering as a hypothesis testing tool; determination of number of clusters; selecting variables to cluster upon; evaluation of clustering performance; alternative clustering methods (sequential, evolutionary, deep, ensemble, etc.)

Proper characterization of uncertainty remains a major challenge and is inherent to many aspects of modelling such as structural development, hypothesis testing and parameter estimation, and the adequate characterization of parameters, forcing data and initial and boundary conditions. To address this challenge, useful methods are uncertainty analysis, sensitivity analysis and inversion (calibration), either in Bayesian, geostatistical or conventional manners.

This session invites contributions that discuss advances, both in theory and/or application, in methods for SA/UA and inversion applicable to all Earth and Environmental Systems Models (EESMs). This includes 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 approaches for parameter estimation, data inversion and data assimilation,
3) Novel methods for spatial and temporal evaluation/analysis of models,
4) Single- versus multi-criteria SA/UA/inversion,
5) The role of data information and error on SA/UA (e.g., input/output error, model structure error, worth of data etc.), and
6) Improving the computational efficiency of SA/UA/inversion (efficient sampling, surrogate modelling, parallel computing, model pre-emption, etc.).

Contributions addressing any or all aspects of sensitivity/uncertainty, including those related to structural development, hypothesis testing, parameter estimation, data assimilation, forcing data, and initial and boundary conditions are invited. We also invite instances of the above research questions applied to scientifically built machine-learning models.

This interdisciplinary session welcomes contributions on novel conceptual and/or methodological approaches and methods for the analysis and statistical-dynamical modeling of observational as well as model time series from all geoscientific disciplines.
Methods to be discussed include, but are not limited to linear and nonlinear methods of time series analysis. time-frequency methods, statistical inference for nonlinear time series, including empirical inference of causal linkages from multivariate data, nonlinear statistical decomposition and related techniques for multivariate and spatio-temporal data, nonlinear correlation analysis and synchronisation, surrogate data techniques, filtering approaches and nonlinear methods of noise reduction, artificial intelligence and machine learning based analysis and prediction for univariate and multivariate time series.
Contributions on methodological developments and applications to problems across all geoscientific disciplines are equally encouraged. We particularly aim at fostering a transfer of new methodological data analysis and modeling concepts among different fields of the geosciences.

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Sub-Session "Mathematical Climatology and Space-time Data Analysis" (Abdel Hannachi, Amro Elfeki, Christian Franzke, Muhammad Latif, Carlos Pires)

The recent progress in mathematical methods to solve various problems in weather & climate nonlinear dynamics and data analysis calls for the need to develop a new session that focus on those methods. Novel and powerful mathematical methods have been developed and used in different subjects of climate. Because those methods are used within specific contexts they go unnoticed most of the time by climate researchers. The proposed new session will provide the opportunity to climate scientists and researchers working on developing mathematical methods for climate to come together and present their findings in a transparent way. This will also be easily accessible to other climate scientists who look for, and are interested in specific methods to solve their problems.
Contributions are encouraged from researchers working on mathematical methods and their application to weather and climate. We particularly welcome contributions on optimization, dimension reduction and data mining, space-time patterns identification, machine learning, statistical prediction modelling, nonlinear methods , Bayesian statistics, and Monte-Carlo Markov Chain (MCMC) methods in stochastic modelling.

Heavy precipitation events in small and medium size catchments can trigger flash floods, which are characterized by very short response times and high specific peak discharges, and often occur in ungauged basins. Under appropriate geomorphological conditions, such rainstorms also cause debris flows or shallow landslides mobilizing large amounts of unconsolidated material. Although significant progress has been made in the management of these different hazards and related risks, they remain poorly understood and their predictability is affected by large uncertainties, due to the fast evolution of triggering rainfall events, the lack of appropriate observations, the high variabilities and non-linearities in the physical processes, and the high variability and complexity of societal vulnerability.
This session aims to illustrate current advances in monitoring, understanding, modelling, and forecasting flash floods and associated geomorphic processes, and documenting and anticipating the societal impacts and social responses.
Contributions on the following scientific themes are more specifically expected:
- Development of new measurement techniques adapted to flash floods and/or rainfall-induced geomorphic hazards monitoring (including in-situ sensors and remote sensing data, such as weather radar, and lightning ..), and quantification of the associated uncertainties,
- Identification of processes leading to flash flood events and/or rainfall-induced geomorphic hazards from data analysis and/or modelling, and of their characteristic space-time scales,
- Possible evolutions in hazard characteristics and frequency related to climate change,
- Development of short-range (0-6h) rainfall forecasting techniques adapted to heavy precipitation events, and representation of associated uncertainties,
- Development of hydro-meteorological forecasting chains for predicting flash floods and/or rainfall-induced geomorphic hazards in gauged and ungauged basins,
- Development of inundation mapping approaches specifically designed for an integration in flash floods monitoring or forecasting chains,
- Use of new criteria such as specific “hydrological signatures” (high water marks, impacts and damages, ..) or other proxy data for model and forecast evaluation,
- Observation, understanding and prediction of the societal vulnerability and social responses to flash floods and/or associated hydro-geomorphic hazards.

Drought and water scarcity are important issues in many regions of the Earth. While an increase in the severity and frequency of droughts can lead to water scarcity situations, particularly in regions that are already water-stressed, overexploitation of available water resources can exacerbate the consequences of droughts. In the worst case, this can lead to long-term environmental and socio-economic impacts. 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 information provided into 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/or 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 explaining them to water managers, policymakers and other stakeholders, are further issues that are addressed. The session aims to bring together scientists, practitioners and stakeholders in the fields of hydrology and meteorology, as well as in the field of water resources and/or risk management; interested in monitoring, modelling and forecasting drought and water scarcity, and in analyzing their interrelationships, hydrological impacts, and the feedbacks with society. Particularly welcome are applications and real-world case studies in regions subject to significant water stress, where the importance of drought warning, supported through state-of-the-art monitoring and forecasting of water resources availability is likely to become more important in the future. Contributors to the session are invited to submit papers to the Special Issue (SI) entitled "Recent advances in drought and water scarcity monitoring, modelling, and forecasting", to be published in the open-access journal Natural Hazard and Earth System Sciences (https://www.natural-hazards-and-earth-system-sciences.net/special_issues/schedule.html). Submission is open until 31 December 2020, for manuscripts that are not under consideration for publication elsewhere.

This session brings together scientists, forecasters, practitioners and stakeholders interested in exploring the use of ensemble hydro-meteorological forecast 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.

The session welcomes new experiments and practical applications showing successful experiences, as well as problems and failures encountered in the use of uncertain forecasts and ensemble hydro-meteorological forecasting systems. Case studies dealing with different users, temporal and spatial scales, forecast ranges, hydrological and climatic regimes are welcome.

The session is part of the HEPEX international initiative: www.hepex.org

This interactive session aims to bridge the gap between science and practice in operational forecasting for different water-related natural hazards. Operational (early) warning systems are the result of progress and innovations in the science of forecasting. New opportunities have risen in physically based modelling, coupling meteorological and hydrological forecasts, ensemble forecasting, impact-based forecasting and real time control. Often, the sharing of knowledge and experience about developments are limited to the particular field (e.g. flood forecasting or landslide warnings) for which the operational system is used.
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 natural hazards. Real-world case studies of system implementations - configured at local, regional and national scales - will be presented, including trans-boundary issues. An operational warning system can include, for example, monitoring of data, analysing data, making forecasts, giving warning signals and suggesting response measures.
Contributions are welcome from both scientists and practitioners who are involved in developing operational forecasting and/or management systems for water-related natural or man-made hazards, such as flood, drought, tsunami, landslide, hurricane, hydropower, pollution etc.

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

Hydrological forecasting can benefit from a better understanding of urban floods and of the thresholds values of the hydrological variables that are crucial for making decisions. This session addresses these two aspects.
Urban flooding is becoming a major issue in many megacities around the world due to a lack of adequate storm water management, hydrologic design, and failure of aging hydrologic infrastructure. To model such extreme flood events, it is of utmost importance to develop state-of-the-art disaster mitigation and damage reduction measures, as well as one and two-dimensional hydrologic and coupled hydrodynamic modelling approaches. Innovative methods are needed to address the modelling and management of urban floods and their spatial and temporal complexity. The session discusses urban floods analysis and measures to mitigate the effects of these events, emerging (e.g., Internet-of-Things (IoT)-based) flood monitoring systems, street-level flood forecasting, dissemination of flood warnings and measures to evacuate people, case studies that provide a better understanding of urban flood management, and innovative methods of floodwater conservation, including strategies and practices to control surface runoff at its sources in a sustainable way.
In hydrological forecasting, where the stochastic nature of the processes makes impossible a deterministic forecast of both the magnitude of the processes and their effects, threshold values can be of great importance and usefulness. Thresholds can be simple (e.g., the threshold of rainfall intensity that might separate stratiform from convective rainfall) or complex and multi-variate (e.g., the threshold for damaging snow-melt flooding, or the threshold for intense hillslope erosion in an agricultural field). They can be useful for real-time forecasts based on simple thresholds on rainfall data (e.g., activation of mass movements such as landslides, debris flow, rill and inter-rill erosion, etc.), for the adoption of satellite data in the management of ground actions (e.g., values of the satellite indexes to be used in irrigation management), for distinguishing among water flow regimes, among other applications.

Statistical post-processing techniques for weather, climate, and hydrological forecasts are powerful approaches to compensate for effects of errors in model structure or initial conditions, and to calibrate inaccurately dispersed ensembles. These techniques are now an integral part of many forecasting suites and are used in many end-user applications such as wind energy production or flood warning systems. Many of these techniques are flourishing in the statistical, meteorological, climatological, hydrological, and engineering communities. The methods range in complexity from simple bias correction up to very sophisticated distribution-adjusting techniques that take into account correlations among the prognostic variables.

At the same time, a lot of efforts are put in combining multiple forecasting sources in order to get reliable and seamless forecasts on time ranges from minutes to weeks. Such blending techniques are currently developed in many meteorological centers.

In this session, we invite presentations dealing with both theoretical developments in statistical post-processing and evaluation of their performances in different practical applications oriented toward environmental predictions, and new developments dealing with the problem of combining or blending different types of forecasts in order to improve reliability from very short to long time scales.