The chemical, physical and biological condition of waterways – “water quality” – is critical for ecological and human health, commerce, food supply, and conflict management. This session shares cutting edge methods, new synthesis products, and new models about water quality. We explore new tools and data sets that reveal spatial and temporal patterns in water quality at scales of catchments and river networks. For example, wide-spread deployment of high-frequency in-situ water quality sensors has revolutionized our understanding of watershed dynamics over diel, storm, and seasonal timescales, highlighting the role of discrete events on annual export. Development of novel sensors for precision water quality measurements along with emerging capabilities for remote sensing of water quality, the explosion in synthesis opportunities from data archives, and improvements in the specificity and parsimony of water quality models enable new understanding of where, when, and why water quality varies, and new theory to explain these patterns.

Hydrologists, biogeochemists, ecologists, and watershed scientists continue to push the envelope within and across their disciplines, generating innovative hydrological and water quality science (e.g., related to nutrients and emerging contaminants) using novel measurement and modeling approaches. Recent advances in in-situ sensor and remote sensing technologies, for example, are generating “big” environmental data with unprecedented temporal resolution and spatial coverage. Access to these data streams has provided strides in scientific understanding and modeling capabilities. However, converting scientific information to real-world action that contributes to improved on-the-ground environmental and water quality management, and fulfills broader impacts of federally funded scientific research, remains a challenge. In this session, we encourage presentations that highlight research at varying stages that aims to apply novel measurements, models, and scientific innovations in hydrology and water quality to real world management solutions across multi-scale watersheds.

Metabolism is the pulse of an aquatic ecosystem as reflected by gross primary production, ecosystem respiration, and net ecosystem production. Increased interest in aquatic metabolism reflects its central importance to nutrient transport and water quality as well as the role of key drivers such as climate and land use changes. Many examples exist in which improved management practices are helping restore a more natural metabolism rate. The increasing availability of high-frequency in-situ sensor measurements in rivers, lakes and estuaries as well as new approaches using remote sensing and drones are facilitating improved metabolism and water quality modeling approaches. We welcome investigations that highlight measurements and modeling of nutrient transport, aquatic metabolism and water quality in inland and coastal settings, and encourage investigators to share new insights into the roles of climate change and other anthropogenic factors.

Nonpoint source (NPS) fluxes in vadose zone, groundwater, and at their interface to surface water are critical to societal issues including agricultural sustainability, food security, drinking water quality, ecosystem health, and global change. Better understanding is needed of bio/geo/hydro/chemical and anthropogenic factors affecting diffuse mass fluxes of nutrients, pesticides, emerging contaminants, trace elements, greenhouse gases and other chemical/biological agents. Strategies are emerging to monitor sources and fate of NPS fluxes and to more effectively control and remediate water quality. We invite contributions assessing NPS transport processes and flow routes using field, laboratory, and modeling approaches across scales; presentations on innovative remediation options to control or intercept NPS pollution in rural or urban settings; on studies that address linkages between chemical, biological, hydro(geo)logical, climatological, and/or social factors affecting NPS fluxes; on monitoring approaches to assess NPS fluxes; and on studies linking agricultural practices to NPS fluxes to develop sustainable management options.

Water quality is under severe threat, from intensive agricultural practices and widespread over-application of commercial fertilizers, to climate change and wildfires threatening our drinking water supplies, to emerging contaminants from rapid urbanization and concentrated livestock operations. Multiple new policies have been developed to improve water quality in our lakes and streams; however, water quality remains a persistent problem. Such apparent failures can be attributed in part to legacy pollutants that has accumulated over decades of agricultural intensification and that can lead to time lags in water quality improvement. Here, we focus on nitrogen legacies. We identify the key knowledge gaps related to landscape nitrogen legacies and propose approaches to manage and improve water quality, given the presence of these legacies.

Accurate estimation of water quality is critical to assess the adverse effects of environmental pollutants on the natural processes of the river systems with changing climate. While there is a growing interest in the community for Machine Learning (ML) models, in many ways, there is still a non-evidence based preference for physical process based models as there is a lack of interpretability and expansibility in terms of applying ML models in real-world application. In this regard, this study aims to develop a ML based methodology that thoroughly addresses the underlying physical science for water quality modeling using Long Short Term Memory (LSTM) approach to predict the changes in the water quality drivers under non-stationary climate conditions. For pilot demonstrating purposes, the methodology will be applied to the Ohio River. The results will show confidence in the application of ML based approaches as well as improvements in understanding of the associated climate uncertainty for assessing the water quality in general.

The accumulation of plastic debris in the environment is an increasing concern. Besides the direct negative effects on human livelihood and (aquatic) ecosystems, land-based plastics are also considered the dominant source of ocean plastic pollution. The understanding of the fate and transport of (micro)plastics within freshwater and terrestrial environments is still at an early stage. In this session, we invite contributions that focus on the study of plastics in freshwater, terrestrial and oceanic systems including, but not limited to: Plastic detection and monitoring techniques; (Long-term) monitoring efforts Source and (bio) accumulation investigations; Transport processes; Prevention, mitigation and reduction; Outreach and stakeholder involvement efforts; We welcome studies focused on all sizes (macro, micro and nano), geographic areas and ecosystems (land, freshwater, estuary, ocean).

Watershed models and associated tools have been continuously improving along with availability of new data to alleviate the increasing environmental concerns and the potential impacts to human society around the world. For example, Harmful Algal Blooms (HABs) in the Great Lakes Region (USA/Canada), soil erosion problems in Loess Plateau (Northern China), and scarcity of water resources in Africa. On the other hand, it is almost impossible to solve challenging tasks without considering cross-surface, cross-scale, or cross-spatial interactions, especially under the threat of global climate change. Compromises in model structure and measurement data are made not only during the modeling processes, but the corresponding water-food-energy nexus should be considered cooperatively. Since 2016, this modeling session has been initiated to provide broad discussions among international scientists from different disciplines. We hope mutual efforts in this session can advocate advanced insights for future investigation on both modeling development and the associated management strategies.

Water management plans depend on accurate and timely watershed modeling and data integration to improve understanding of a broad range of environmental and societal water issues across spatial and temporal scales. Continued and evolving advances in watershed modeling are needed to address concerns related to water availability (quantity and quality) and to provide timely information to scientists, managers, and policy makers. This session seeks interdisciplinary discussion of modeling and data developments and their applications to solve water management related problems. We invite contributions focused on 1) innovations in the development of new, or improvements to existing, hydrologic or water-quality models (e.g., representation of water demand and consumption, incorporation of lag times, dealing with impacts of climate changes), 2) novel uses of hydrologic or water-quality models to support water management and communication, and 3) creative approaches for model and data integration, including machine learning methods, across spatial and temporal scales.

This multidisciplinary session focuses on understanding the local- to global-scale effects of lakes and inland water bodies on Earth’s biosphere, hydrosphere, and atmosphere using modelling techniques, historical records, observation-based datasets, and GIS and remote sensing tools. We also welcome abstracts covering the policy and management of inland water bodies as a critical water resource and with significant economic potential. The topics include:

Limnology (physical, chemical, and/or biological properties; lake geology and geological records; lake ecosystems and human interactions; anthropogenic impacts e.g., acidification and eutrophication; etc.)

Data and modeling (lake models; ecological modelling; GIS and remote sensing; observations (e.g., buoy data); development of new datasets; etc.)

Lake hydrology (lake levels; lake watersheds; etc.)

Lake - atmosphere interactions (lake-effect precipitation and lake-induced storms; diurnal and seasonal temperature modulation; microscale and mesoscale climate effects; boundary layer modifications; etc.)

Effects of climate change on inland water bodies

Policy and management

Wildfires are ubiquitous among Earth’s major ecosystems, resulting in effects on vegetation, soils, water quantity, water quality, hillslope and fluvial geomorphic processes, organisms, and human activities. Following a wildfire, removal of vegetation combined with changes to soil physical and chemical properties can result in shifts in controlling processes such as soil water dynamics, streamflow generation, soil erodibility, and surface energy balances. These process changes have consequences for water, carbon, sediment, and nutrient fluxes across large ranges of spatial and temporal scales. This session will emphasize point- to landscape-scale impacts of wildfire on hydrologic, geomorphic, biogeochemical, and ecological processes. We also look forward to contributions that discuss the needs and direction of our research community. This session welcomes the opportunity to highlight research across diverse geographic locations and will include a virtual component to encourage remote participation. We encourage abstracts that creatively highlight field or laboratory experiments using virtual technologies.

Statistical, analytical and numerical models are often used to simulate a wide array of hydrologic and water quality processes. But these models are subject to a number of uncertainties, impacting their reliability and utility for subsequent management decisions. As a result, stochastic approaches for estimating the fields of and uncertainties around key hydrologic and water quality variables are desired. Here, we focus on submissions that: (a) contribute to recent research on uncertainty analysis, particularly in monitoring, modeling and management, and/or (b) studies that approach hydrologic and water quality modeling more generally from a stochastic standpoint (e.g., parameterization methods; probability-based forecasts; assessment of extremes in current and future climates). We also encourage submissions focused on the communication of probabilistic forecasts and uncertainty/risk estimation with stakeholders and decision makers. This session will be of interest to engineers, hydrologists, statisticians, watershed managers and regulators.

Groundwater-surface water (GW-SW) interfaces (e.g., hyporheic zones, riparian corridors, floodplains, and wetlands) often function as biogeochemical and ecological hotspots. They fundamentally regulate the storage, conveyance, and transformation of mass and energy as materials are transported from headwaters to oceans. Characterizing GW-SW requires understanding coupled interactions between hydro-bio-geochemical processes and how these processes and interactions vary across spatial and temporal scales. Predicting the local and cumulative role these interactions play on processes such as nutrient cycling, contaminant transformation, thermal and flow regulation, microbial metabolism, particle transport, and habitat structure, requires an interdisciplinary approach integrating principles from hydrology, geomorphology, biogeochemistry, and aquatic ecology. This 12th-annual GW-SW session aims to bring together the broad community of researchers to facilitate an integrated, multidisciplinary representation of GW-SW processes across varying systems and scales, based on novel field, laboratory, and/or modeling approaches.

Water quality parameters such as stream temperature, dissolved oxygen, and sediment concentration play a vital role in the life cycle and distribution of aquatic species and determine the suitability of water resources for human use. Rising air temperature and changes in precipitation will alter water quality by varying the hydrologic sources contributing to streams and can also change in-stream chemical processes. This session will examine the impacts of historical or projected climate variability and change on stream water quality. We welcome observational and modeling studies that examine the interactions of hydrology and relevant physical and chemical processes at all spatial and temporal scales.