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Flood forecast combining hydrological modelling and Machine Learning

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.

 Lecture slides...