Improving continental and global scale digital elevation models via estimation of a riverine topobathymetric surface

Abstract

Contemporary continental and global-scale digital elevation models (DEMs) are not a composite topobathymetric surface, as they tend to lack bathymetry. In this study, we analyzed if continental- and global-scale DEMs can be improved using a global hydrologic model and simple steady-state hydraulic techniques. We used two DEM datasets, globally available streamflow estimates, and simple hydraulic and mapping software to perform the analysis. We analyzed two distinct means by which to estimate bathymetry: the use of bank elevations and bankfull discharge estimates and the use of water surface elevation (WSE) and baseflow estimates to estimate bathymetry. We also introduced and investigated a new method for pre-cleaning the DEM prior to estimating a bathymetry. We found that the error and bias of a DEM can consistently be reduced using a global hydrologic model's streamflow and simple hydraulic analysis by using the DEMs WSE estimate and a baseflow to estimate the topobathymetric surface.