The product of our research and development, Floodly uses machine learning methods to predict river levels and predict flood risk using only precipitation data. Floodly’s rapid predictions complement traditional hydraulic modelling, which can be slower and more costly to apply. It is also challenging in complex urban catchments.
Location
- United Kingdom
Project status
- Proof of concept
In the catchments we examined we can select a specific time period and get a prediction of river level and timing within seconds. This is a task that typically takes minutes, hours or even days with traditional modelling.”
The Floodly tool uses precipitation data to predict river levels
Catchments modelled
5
Prediction time
<10 sec
Years of data matched
15
Floodly was demonstrated at the Environment Agency’s Flood Warning Hack in November 2019 as a potential solution to the problem of generating flood warnings in hard-to-reach locations. Judges at the Hack were impressed with how Floodly could turn rainfall forecasts into river level predictions, even in catchments with very limited hydrometric data records. The machine learning element, with the potential to automatically refine and improve forecasts through time, was a further interesting development. Floodly was shortlisted to be considered for a trial as part of the Environment Agency’s Flood Warning Expansion Project (FWEP) Discovery phase.
