IRENE : Radar imaging for water level estimation

Floods are a recurring phenomenon in Quebec and, as with any extreme climatic event, the risk is likely to be influenced by climate change. It is in this context that Ouranos supports the INFO-Crue program (administered by the MELCCFP), which was created to optimize the delimitation of flood-prone areas in Quebec and to set up a real-time flood forecasting system. By using satellite radar images, which cover Quebec at an almost daily frequency and are available free of charge (thanks to Sentinel-1 and the RADARSAT Constellation Mission), the project aims in particular to meet the need for water level measurements in river sectors that are not gauged, by creating virtual measurement stations.

• To develop an operational satellite-based approach to create virtual water level stations from satellite radar images, without direct measurements taken in the field

• To estimate water levels in ungauged sectors

• To identify the spatial scope of application (optimal conditions and promising sectors) and detail the technical limitations of the method

• To develop a prototype of an information technology-based tool to apply the method developed

• Establishment of the database (radar images, lidar data, validation data such as level and flow measurements, water lines during floods)

• Selection of optimal sites for the development of the approach, i.e. sites that experienced flooding in 2019, for which validation data exists, which have sufficient satellite radar coverage and which have open banks and clear floodplains

• Classification of the probability of water on radar images of optimal sites at 10 m spatial resolution

• Disaggregation of this map using lidar data and the height above nearest drainage (HAND) model to obtain a map of water presence at 1 m spatial resolution 

• Estimation of water levels and validation of results at optimal sites

• Calculation of uncertainty 

• Automation of process steps

Ultimately, this project will make it possible to set up virtual water level measurement stations on ungauged river sections. The direct results of the project are:

• An approach for estimating water level from radar satellite imaging

• Identification of the factors required for a site to be optimal for implementing the approach

• Detailed knowledge of the approach’s accuracy and uncertainty (radar sensitivity, classification accuracy, HAND sensitivity and disaggregation)

• A prototype (Python Scripts) that the MELCCFP can evaluate internally