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. Machine learning provides a particular approach to this research problem – we’ve put together a list of sessions that emphasizes machine learning.
H093 – Machine Learning in Hydrologic Modeling
https://agu.confex.com/agu/fm19/prelim.cgi/Session/75246
NG004 – Data Assimilation meets Machine Learning
https://agu.confex.com/agu/fm19/prelim.cgi/Session/77631
IN033 – Incorporating physics and domain knowledge to improve interpretability, explainability, reliability and generalization of Machine Learning Models (MLM) in the geosciences
https://agu.confex.com/agu/fm19/prelim.cgi/Session/82358
Domain-specific problems
H045 – Domain-Aware Machine Learning for Subsurface Applications
https://agu.confex.com/agu/fm19/prelim.cgi/Session/85474
H138 – Utility of Artificial Intelligence/Machine Learning Approaches in Soil Hydrological Processes and Agriculture
https://agu.confex.com/agu/fm19/prelim.cgi/Session/74487
H002 – Advances and Applications of Data Integration, Inverse Methods, and Machine Learning in Hydrogeophysics
https://agu.confex.com/agu/fm19/prelim.cgi/Session/71766
S015 – Extracting Information from Geophysical Signals with Machine Learning
https://agu.confex.com/agu/fm19/prelim.cgi/Session/80960
S017 – Geophysical inversion, inference and imaging in the age of machine learning
https://agu.confex.com/agu/fm19/prelim.cgi/Session/80845
U009 – Data Analytics and Machine Learning Innovation for Climate and Earth Surface Processes
https://agu.confex.com/agu/fm19/prelim.cgi/Session/83451
EP027 – Machine Learning Applications in Earth Surface Processes Research
https://agu.confex.com/agu/fm19/prelim.cgi/Session/75302
In other fields
GC006 – AI and Machine Learning for Climate and Extreme Weather Prediction
https://agu.confex.com/agu/fm19/prelim.cgi/Session/81937
A137 – Use of Machine Learning and Causal Discovery to Advance Knowledge in the Atmospheric Sciences – Methods, Limitations and Trade-offs
https://agu.confex.com/agu/fm19/prelim.cgi/Session/76723
A091 – Machine Learning for Climate Modeling and Inference
https://agu.confex.com/agu/fm19/prelim.cgi/Session/78836
GC076 – Solar Radiation Monitoring and Forecast from Satellite Observations and Models: Physical and Machine Learning Perspectives
https://agu.confex.com/agu/fm19/prelim.cgi/Session/81059
NG007 – Machine Learning in Space Weather
https://agu.confex.com/agu/fm19/prelim.cgi/Session/72833
SH015 – Machine Learning and Data Assimilation as Emerging Tools for Characterization and Forecasting of Solar Variability and Space Weather Events
https://agu.confex.com/agu/fm19/prelim.cgi/Session/80120
P022 – Machine Learning for Planetary Science
https://agu.confex.com/agu/fm19/prelim.cgi/Session/78481
OS019 – Innovation and Exploration with Machine Learning in Ocean and Atmospheric Sciences: Global and Regional Applications
https://agu.confex.com/agu/fm19/prelim.cgi/Session/85463