Exponentially cascaded cross-sectional volume estimates from elevation data

The relationship between discharges and flow heights is a critical component of hydraulic modelling, often carried out involving data on the elevation profiles of the river bed. However, obtaining and using cross-sectional profile data can be resource intensive. Methods for profile estimation from rasterized elevation and bathymetry can help overcome this. In this paper, an efficient algorithm for cross-sectional estimates of discharge-volume relationships is presented as part of the FastFlood method. The method uses exponentially cascading to estimate profiles efficiently with lower resolution further away from the channel center-lines. Two study cased are presented, the Sunkoshi River in North Nepal, and the Rhine river at the border between Germany and the Netherlands. For these areas the discharge-volume relationship is compared for a full 2D hydrodynamic model, the Fastflood method and an estimate through Mannings equation using cross-sectional area and wetted perimeter. We observe a similar match between the model setups, with deviations within a 5% percent range. There is an excellent estimation of general flow depths with the improved FastFlood methodology. Moreover, the application of a localized estimate of Manning’s flow law can provide flow velocities, but limitations remain due to the absence of inertia in the Fastflood model.