Floods are among the most catastrophic natural disasters with great destructive impact that
happen suddenly and sometimes unexpectedly. Although advanced technological tools are
available for extreme events prediction, a significant number of floods and inundations still
occur every year around the world, causing thousands of deaths and heavy economic losses.
Climate change adds uncertainty and severity to intense precipitation phenomena, making it
increasingly important to forecast their potential effects in a timely manner in order to
minimize their impacts. Recently, the great progress in computational resources and
modelling advances, as well as the increase of satellite remote sensing data provided new
opportunities to create powerful hydroinformatic tools to be used in the implementation of
flood forecasting and warning systems. These developments also benefit from the availability
of real-time meteorological information, especially from satellite-based weather radar and
meteorological radar and from a diverse range of atmospheric models forecasts that allow
their use to force hydrological and hydrodynamic models. This study describes the
incorporation of meteorological and hydrological data and models for a flood forecasting
and early warning system implementation based on the Delft FEWS platform. The
Portuguese river Ave basin was taken as study area. This platform, besides early warnings
emissions, will help decision makers and planners to identify areas of potentially significant
flood risk, and then the preparation of flood risk management plans, and to set out
emergency preparedness plans for these areas.