- How can AI and ML algorithms enhance our predictive capabilities in hydrology, leading to more accurate forecasts of water availability and quality?
- Are there any ongoing projects or research initiatives using AI/ML in hydrology that you find particularly inspiring?
Very interesting questions, Max! Of course, many studies are working on the use of Machine Learning (ML) in hydrological modeling. I can think of some water quantity applications:
And many more.
One recent research project I am currently working on involves the use of ML to predict model parameters using soil information for distributed hydrological modeling. This means predicting parameter values using a transfer function instead of the traditional model calibration, thus saving a significant amount of time and enabling large-scale modeling.
I hope this helps, and wish you the best of luck.
Awad M. Ali
AI and ML enhance hydrology by processing diverse data, improving models, enabling real-time forecasting, quantifying uncertainty, and automating feature selection. Inspiring initiatives include NASA's Earth Science Division, HydroNET in the Netherlands, and NCAR's work on weather predictions. These technologies hold promise for more accurate water forecasts.
Dear colleagues,
There are only 8 days left to submit an abstract for our upcoming session at the European Geosciences Union General Assembly (EGU) 2024 entitled "HS8.2.4 - Advanced Groundwater Modeling: Cross-breeding Classical Models and Artificial Intelligence". This session expects to bring together experts from hydrogeology, artificial intelligence (AI), and water resources management to discuss the future path of physically-based groundwater models and explore the potential of surrogate models, as well as hybrid models that combine AI techniques with classical numerical and empirical groundwater ones. The session offers a unique opportunity to foster interdisciplinary collaborations and the exchange of ideas and experiences related to AI-driven approaches combined with classical methods. Session Details: https://meetingorganizer.copernicus.org/EGU24/session/48387
Conveners: Carolina Guardiola-Albert, Héctor Aguilera, Emmanouil Varouchakis, Jaime Gómez-Hernández • Abstract Submission Deadline: January 15, 2024 • EGU General Assembly Dates: April 23-28, 2024 • Location: Vienna, Austria We look forward to your contributions and the opportunity to engage in fruitful discussions at the EGU General Assembly in Vienna. Please feel free to contact us if you have any questions or require further information about the session.
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