Remote Estimation of River Discharge and Bathymetry: Sensitivity to Turbulent Dissipation and Bottom Friction

We investigated the fidelity of a hierarchy of inverse models that estimate river bathymetry and discharge using measurements of surface currents and water surface elevation. Our most comprehensive depth inversion was based on the Shiono and Knight (1991) model that considers the depth-averaged along-channel momentum balance between the downstream pressure gradient due to gravity, the bottom drag and the lateral stresses induced by turbulence. The discharge was determined by minimizing the difference between the predicted and the measured streamwise variation of the total head. The bottom friction coefficient was assumed to be known or determined by alternative means. We also considered simplifications of the comprehensive inversion model that exclude the lateral mixing term from the momentum balance and assessed the effect of neglecting this term on the depth and discharge estimates for idealized in-bank flow in symmetric trapezoidal channels with width/depth ratio of 40 and different side-wall slopes. For these simple gravity-friction models, we used two different bottom friction parameterizations - a constant Darcy-Weisbach local friction and a depth-dependent friction related to the local depth and a constant Manning (roughness) coefficient. Our results indicated that the Manning gravity-friction model provides accurate estimates of the depth and the discharge that are within 1% of the assumed values for channels with side-wall slopes between 1/2 and 1/17. On the other hand, the constant Darcy-Weisbach friction model underpredicted the true depth and discharge by 7% and 9%, respectively, for the channel with side-wall slope of 1/17. These idealized modeling results suggest that a depth-dependent parameterization of the bottom friction is important for accurate inversion of depth and discharge and that the lateral turbulent mixing is not important. We also tested the comprehensive and the simplified inversion models for the Kootenai River near Bonners Ferry (Idaho) using in situ and remote sensing measurements of surface currents and water surface elevation obtained during a 2010 field experiment.