Flood forecast combining hydrological modelling and Machine
Competency Framework
WMO Satellite Skills
Application
Description
Boris Gratadoux presents an automatic flood forecast tool that combines two kinds of information used as input of a Machine Learning algorithm.
Content
Thales has developed an automatic flood forecast tool combining two kinds of information used as input of a Machine Learning algorithm:
- - Forecasted flows at the outlet of the watershed of interest, obtained with an ensemble data assimilation using a particle filter;
- - Current soil state information from space-based observations;
The prototype allows forecasting time series of flood occurrence associated with a confidence index for a 6-day flood forecast with a 6-hour time-step. It has been tested and validated on a French watershed with good results.