Y. Shimizu | USGS Science

USGS2012

Using computational modeling of river flow with remotely sensed data to infer channel bathymetry

As part of an ongoing investigation into the use of computational river flow and morphodynamic models for the purpose of correcting and extending remotely sensed river datasets, a simple method for inferring channel bathymetry is developed and discussed. The method is based on an inversion of the equations expressing conservation of mass and momentum to develop equations that can be solved for depth given known values of vertically-averaged velocity and water-surface elevation. The ultimate goal of this work is to combine imperfect remotely sensed data on river planform, water-surface elevation and water-surface velocity in order to estimate depth and other physical parameters of river channels. In this paper, the technique is examined using synthetic data sets that are developed directly from the application of forward two-and three-dimensional flow models. These data sets are constrained to satisfy conservation of mass and momentum, unlike typical remotely sensed field data sets. This provides a better understanding of the process and also allows assessment of how simple inaccuracies in remotely sensed estimates might propagate into depth estimates. The technique is applied to three simple cases: First, depth is extracted from a synthetic dataset of vertically averaged velocity and water-surface elevation; second, depth is extracted from the same data set but with a normally-distributed random error added to the water-surface elevation; third, depth is extracted from a synthetic data set for the same river reach using computed water-surface velocities (in place of depth-integrated values) and water-surface elevations. In each case, the extracted depths are compared to the actual measured depths used to construct the synthetic data sets (with two- and three-dimensional flow models). Errors in water-surface elevation and velocity that are very small degrade depth estimates and cannot be recovered. Errors in depth estimates associated with assuming water-surface velocities equal to depth-integrated velocities are substantial, but can be reduced with simple corrections.

Conference Paper↗

USGS2011

Bedform response to flow variability

Laboratory observations and computational results for the response of bedform fields to rapid variations in discharge are compared and discussed. The simple case considered here begins with a relatively low discharge over a flat bed on which bedforms are initiated, followed by a short high-flow period with double the original discharge, during which the morphology of the bedforms adjusts, followed in turn by a relatively long period of the original low discharge. For the grain size and hydraulic conditions selected, the Froude number remains subcritical during the experiment, and sediment moves predominantly as bedload. Observations show rapid development of quasi-two-dimensional bedforms during the initial period of low flow with increasing wavelength and height over the initial low-flow period. When the flow increases, the bedforms rapidly increase in wavelength and height, as expected from other empirical results. When the flow decreases back to the original discharge, the height of the bedforms quickly decreases in response, but the wavelength decreases much more slowly. Computational results using an unsteady two-dimensional flow model coupled to a disequilibrium bedload transport model for the same conditions simulate the formation and initial growth of the bedforms fairly accurately and also predict an increase in dimensions during the high-flow period. However, the computational model predicts a much slower rate of wavelength increase, and also performs less accurately during the final low-flow period, where the wavelength remains essentially constant, rather than decreasing. In addition, the numerical results show less variability in bedform wavelength and height than the measured values; the bedform shape is also somewhat different. Based on observations, these discrepancies may result from the simplified model for sediment particle step lengths used in the computational approach. Experiments show that the particle step length varies spatially and temporally over the bedforms during the evolution process. Assuming a constant value for the step length neglects the role of flow alterations in the bedload sediment-transport process, which appears to result in predicted bedform wavelength changes smaller than those observed. However, observations also suggest that three-dimensional effects play at least some role in the decrease of bedform wavelength, so incorporating better models for particle hop lengths alone may not be sufficient to improve model predictions.

Earth Surface Processes and Landforms↗