Available on-demand
Unlocking the power of global flood maps
Thursday, October 23, 2025 – 16:00 – 17:00 BST
Advancing flood and climate modeling with machine learning
Machine learning is a powerful technology but it’s not a universal solution. Understanding its potential, limitations and effective applications is crucial.
Following on from Part 1: An introduction to machine learning, and Part 2: The future of terrain data, this webinar explores the intersection of machine learning and hydrology, with a focus on global-scale flood and climate modeling.
You’ll learn about the challenges of building climate-conditioned flood models, the role of machine learning in innovating hydrological science and its application in real-world scenarios. Participants will gain insights into using machine learning for rainfall prediction, hydraulic modeling and addressing data scarcity and quality issues.
In this webinar, we explore:
- The fundamentals of global flood and climate modeling
- The science behind these models
- The role of machine learning in hydrology and climate science
- Access to essential datasets for hydrological modeling
- Applications of machine learning in data-scarce and poor-quality data regions
- Future trends in machine learning-driven flood and climate modeling
This webinar is part of a three-part training series, accredited by CIWEM, exploring the transformative role of machine learning in flood modeling. It highlights how machine learning improves uncertainty management, enhances modeling accuracy and supports early decision-making for adaptation and resilience. Explore the other webinars in this series:
Other webinars in this series
Part 1: An introduction to machine learning
We’ll break down the fundamentals of machine learning – what it is, how it works and the reasons behind its growing popularity. We’ll explore real-world applications in flood and climate modeling and examine emerging trends that are driving innovation and shaping the future of hydrological modeling. In this webinar, our experts will explore:
- The fundamentals of machine learning
- Guiding principles of machine learning, its role, strengths and limitations
- How machine learning can be used in flood and climate modeling
- Emerging trends and future applications
Part 2: The future of terrain data
We delve into the intersection of machine learning and terrain data, exploring how cutting-edge techniques are reshaping the way we analyze and utilize geographical information. We will cover:
- Terrain data basics: Types, challenges and applications
- Machine learning in terrain data: Opportunities, tasks and limitations
- Collaboration: Integrating machine learning with geographical expertise
- Fathom’s approach: Methods and evaluation principles
- Real-world applications: Flood modeling, urban planning and more
- Future trends: Emerging tech and innovations in machine learning
