The Hydrologic Uncertainty Technical committee’s mission includes three “big research questions”. The second is “How to reduce uncertainty in understanding, modelling, and predicting the future of coupled human-hydrologic systems?” We’ve put together a list of sessions that emphasizes this research problem. We also have a list of sessions specifically using machine learning techniques.
Improving modelling and watershed science
H098 – Modeling hydrological processes and changes under a changing environment
https://agu.confex.com/agu/fm19/prelim.cgi/Session/77780
H023 – Advancing watershed science using machine learning, diverse data, and mechanistic modeling
https://agu.confex.com/agu/fm19/prelim.cgi/Session/83085
Domain-specific problems
H092 – Long-Term Climate Modeling and Hydrological Projection
https://agu.confex.com/agu/fm19/prelim.cgi/Session/78073
H067 – GRACE / GRACE-FO Applications in Terrestrial Hydrology
https://agu.confex.com/agu/fm19/prelim.cgi/Session/80807
H064 – Geogenic Contamination in the Groundwater System: Advances (and Challenges) in Assessment, Water Quality Modeling, Uncertainty, and Water Supply Management
https://agu.confex.com/agu/fm19/prelim.cgi/Session/85455
H013 – Advances in quantifying impacts and extents of land-use/land-cover change on hydrology.
https://agu.confex.com/agu/fm19/prelim.cgi/Session/72615
GC057 – Multi-scale, Multi-Region, and Multi-Actor Interactions for Sustainability and Resilience in the Food-Energy-Water Nexus
https://agu.confex.com/agu/fm19/prelim.cgi/Session/80748
H102 – Nonstationary Impacts on Urban Watersheds
https://agu.confex.com/agu/fm19/prelim.cgi/Session/76386
H126 – Statistical Methods for Modeling Changes in Flood Characteristics: Novel Approaches and Comparisons
https://agu.confex.com/agu/fm19/prelim.cgi/Session/81731[CX1]
In other fields
GC014 – Climate Science in the Age of Deep Learning and Machine Learning
https://agu.confex.com/agu/fm19/prelim.cgi/Session/75997
A055 – Deep Learning for improving short-term atmospheric modeling and prediction
https://agu.confex.com/agu/fm19/prelim.cgi/Session/81500
B081 – Narrowing uncertainty in GHG emissions using UAV (unmanned aerial vehicle) platforms
https://agu.confex.com/agu/fm19/prelim.cgi/Session/79284
A111 – Reducing uncertainty in aerosol effects on climate
https://agu.confex.com/agu/fm19/prelim.cgi/Session/76712
A136 – Urban Climate Informatics — from sourcing to (deep) learning
https://agu.confex.com/agu/fm19/prelim.cgi/Session/81563
IN002 – Advanced Geospatial Cyberinfrastructure for Deep Learning
https://agu.confex.com/agu/fm19/prelim.cgi/Session/74455
H038 – Conventional and Enhanced Geothermal Systems: Characterization, Integration, Stimulation, Simulation, and Induced Seismicity
https://agu.confex.com/agu/fm19/prelim.cgi/Session/80861
GC039 – Four Decades and Counting: NASA Earth Observations and Agricultural Monitoring
https://agu.confex.com/agu/fm19/prelim.cgi/Session/80239
A116 – Seasonal to Multi-Seasonal Earth System Prediction and its Applications
https://agu.confex.com/agu/fm19/prelim.cgi/Session/81965
GC068 – Quantifying impacts in socio-environmental systems through the application of remote sensing and machine learning
https://agu.confex.com/agu/fm19/prelim.cgi/Session/77863