Primary Convener:
Jared Smith, U.S. Geological Survey

Convener:
Noel Aloysius, University of Missouri
Stefan Krause, University of Birmingham
Audrey Sawyer, The Ohio State University
Dylan Blaskey, University of South Carolina
Yan Zheng, Southern University of Science and Technology
Moussa Yatta, University of Missouri
Neil Fox, University of Missouri Columbia

Early Career Convener:
Tim Stagnitta, USGS New York Water Science Center

Chair:
Zachary Johnson, US Geological Survey
Janet Barclay, United States Geological Survey
Joel Blomquist, U.S. Geological Survey
Jennifer Murphy, USGS Tennessee Water Science Center

The need for reliable short- and medium-term forecasts of ecologically significant water quality parameters such as nitrates, salinity and dissolved oxygen in aquatic environments has driven advances in observational and monitoring methods, coupled with process-guided modeling techniques. Yet challenges remain to obtain reliable predictions across a range of hydrologic conditions at spatial and temporal scales that are relevant for decision making. Additionally, the mechanisms controlling the activation and transport of pollutants and the impacts of human interventions, land and water management are poorly understood. This is especially true for the groundwater – surface water interfaces, which represent hotspots of environmental pollution. The temporal dynamics of surface water pollutants interacting with heterogeneous subsurface strata is rather complex. This session invites contributions that explore the potential of combining monitoring, observation, process, and modeling studies with a goal of improving water quality forecasts in surface and subsurface hydrological systems.

Index Terms
1830 Groundwater|surface water interaction
1831 Groundwater quality
1871 Surface water quality
1942 Machine learning

Cross-Listed:
IN - Informatics
B - Biogeosciences
GC - Global Environmental Change

Suggested Itineraries:
Machine Learning and AI

Co-Sponsored Sessions:
EGU： European Geosciences Union

Neighborhoods:
3. Earth Covering