Department of the Interior U.S. Geological Survey

1. Computational Modeling of Bedform Evolution in Rivers with Implications for Predictions of Flood Stage and Bed Evolution Jonathan Nelson1, Yasuyuki Shimizu2, Sanjay Giri3 Richard McDonald1 1. USGS Geomorphology and Sediment Transport Laboratory, Golden, Colorado, USA 2. Department of Civil Engineering, University of Hokkaido, Sapporo, Japan 3. Deltares, Delft, The Netherlands Department of the Interior U.S. Geological Survey

2. Talk Outline • Bedform modeling • Reach-scale morphodynamic modeling • Why we need to put them together • How we are combining them • Example computation for the Kootenai River in Idaho, USA

3. Bedform Modeling • Detailed high spatial and temporal resolution flow model (DNS, LES, RANS): ∆t << 1s, 0.5mm < ∆x,z < 0.01λ,D • Computational models for bedload and suspended load prediction including time variation and disequilibrium effects • Time stepping to predict bedform evolution

7. River Flow and Morphodynamics Modeling • Relatively low spatial and temporal resolution flow model (RANS w/simple closure, 2d VA, quasi-3d, quasi-steady): 1min < ∆t < days, 1m < ∆x,z < 0.1w,D • Computational models for bedload and suspended load prediction • Time stepping to predict evolution of bars and, in some cases, planform geometry wwwbrr.cr.usgs.gov/gstl

8. Flow and morphologic change with FastMech Knik River

9. Why do we need to couple the approaches? • River reach morphodynamics models treat bedforms through specification of roughness, scales and methods of modeling prohibit prediction of bedform behavior • If bedforms change over time, calibration of roughness is required or both flow and morphodynamics will be incorrect • In cases where such data is unavailable, flood inundation, velocity fields, sediment transport and bed change can be predicted incorrectly by river morphodynamics models

10. How do we couple the approaches? • Statically- Use the bedform model along slices of the observed bedform fields to predict roughness and form drag and use those to drive the morphodynamics model • Dynamically- Use the observed hydrograph to predict the evolution of the bedforms and hence the time-varying roughness and form drag values for use in the morphodynamics model • Iterate as required ……A simple field example

11. Meandering Reach - 22 Kilometers Slope ~ 0.00004 Grainsize D50 = 0.22 mm Depth ~ 7.5 meters Velocity ~ 0.5 m/s Braided Reach – 10 Kilometers Slope ~ 0.005 Grainsize D50 = 20mm Depth 3 meters Velocity ~ 1.5 m/s

12. Calibrated Drag Coefficient

13. Typical Kootenai Bedforms

14. Drag Coefficient

15. Rouse Number

16. 2006 Flood Hydrograph

18. Water-Surface Elevation

19. 2006 modeled channel evolution during spring high flow • 75 meter wide X 200 meter long zone of greater than 1 meter of erosion. • Smaller patches of greater than 2 meters of erosion.

21. Conclusions Coupling small-scale bedform models with larger-scale river reach morphodynamics models is tractable The method can be used statically to determine roughness and form drag for river model applications The method can be applied dynamically to include the effects of bedform change over time In at least some cases, predictions are sensitive to the details of temporal bedform evolution