Flood hazard data provide an indication of the magnitude and probability of flooding. These data offer spatially static views of hazard (e.g. the 1-in-100 year flood everywhere)
To model flood hazard correctly, you need a range of hyper-resolution datasets and an understanding of relevant physical processes, including topography, channel locations and sizes, and the physics of flood wave propagation through channels and across floodplains.
In some areas of the world, such as the UK, there is a rich body of data that enables the creation of high-resolution, high-accuracy flood hazard datasets. However, in many other regions, data is scarce and so producing large-scale flood models that accurately represent these flood hazards is much more complex.
Fathom’s Flood Hazard Data & Maps
Fathom’s datasets solve some of the greatest challenges facing flood mapping and hydrology
The key components of building flood hazard datasets at a global scale
Terrain data
These datasets define the topography of the Earth’s ground surface.
Data used
Fathom’s models are underpinned by the best globally available terrain datasets for flood modelling. Our global base data are currently being upgraded from MERIT-DEM to a new dataset based on the Forest and Buildings Removed Copernicus DEM (FABDEM). Our team collaborated in the creation of both ground-breaking datasets. Over certain parts of the globe even higher quality national terrain datasets are available, usually underpinned by laser altimeter data (LiDAR) or photogrammetry derived datasets. Wherever possible these national data are used, including across all of our country specific models.
Discharge estimation
Estimates of extreme river flows to drive the flood inundation model.
Data used
River discharge measurements from thousands of stream gauges globally in a statistical model alongside a multitude of other geospatial datasets.
River channels
Representation of the location and size of all rivers is a critical component in building accurate inland flood models.
Data used
MERIT Hydro globally, more accurate national data (e.g. NHD in US) where available, with our dynamic channel solver used to estimate bathymetry.
Automation
Large scale models must be automated. Manual building of models requires significant time and resource making it impossible to reproduce at continental and global scales.
Data used
Rapid algorithms developed in house by Fathom’s hydrologists.
Efficient inundation modelling
Equations that describe the movement of water quickly, yet with sufficient accuracy.
Data used
A hydraulic model developed across two decades at the University of Bristol by, now, Fathom scientists. By virtue of our open methods, most leading flood modellers throughout the world use some variant of this code.
Related research
Urbanizing the floodplain: global changes of imperviousness in flood-prone areas
Social inequalities in climate change-attributed impacts of Hurricane Harvey
Assessing flooding impact to riverine bridges: an integrated analysis
Increased population exposure to Amphan-scale cyclones under future climates
Inequitable patterns of US flood risk in the Anthropocene
Flood Inundation Prediction
