Organized by:
MASTER CLASSES
WHEN & WHERE
Monday, June 3 2024, 09:00 - 18:00.
Venue of the Congress
ORGANIZERS
The Master Classes will be held the day before the opening of the conference.
Master Classes will be proposed by senior scientists who will be responsible for the organization of the session, including the programme, presentations and other related material. To encourage discussion and audience participation, it is desirable that Master Classes include case studies and practical applications. The duration of each Master Class must not exceed 3.5 hours.
WHO CAN JOIN THE MASTER CLASSES?
All registered IAHR2024 participants are eligible. However, priority will be given to students and young professionals.
LANGUAGE
English
HOW TO REGISTER
Please register through your account area ("Participant Registration Details") in the planned Master Classes.
If you would like to organize a Master Class, please fill in the following proposal form, until November 17, 2023.
Closed!
Machine Learning Approaches for Hydrologic Modeling |
CFD modeling of hydraulic structures with OpenFOAM |
Web-based numerical modelling of managed aquifer recharge applications |
Teaching and working in the cloud with Copernicus products: A hands-on tutorial for learning the usefulness of cloud computation for collaboration and teaching on a study case. |
June 3, 09:00-12:30
Conveners
Ramesh Teegavarapu, Florida Atlantic University, U.S.A.
Description
This Master class aims to introduce the concepts of Machine Learning (ML) approaches for hydrologic modeling and data quality assessment and improvement.
The class will focus on the fundamentals of ML techniques for hydrologic forecasting, data quality improvement, and approaches supporting water resources management.
Observations
Participants should bring their own laptops.