Sediment transport of fine sand to fine gravel on transverse bed slopes in rotating annular flume experiments
Baar, A.W.; de Smit, J.; Uijttewaal, W.S.J.; Kleinhans, M.G. (2018). Sediment transport of fine sand to fine gravel on transverse bed slopes in rotating annular flume experiments. Water Resour. Res. 54(1): 19-45. https://doi.org/10.1002/2017WR020604
In: Water Resources Research: a Journal of the Sciences of Water. American Geophysical Union: Washington etc.. ISSN 0043-1397; e-ISSN 1944-7973, more
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| Authors | | Top |
- Baar, A.W.
- de Smit, J., more
- Uijttewaal, W.S.J.
- Kleinhans, M.G., more
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| Abstract |
Large-scale morphology, in particular meander bend depth, bar dimensions, and bifurcationdynamics, are greatly affected by the deflection of sediment transport on transverse bed slopes due to gravityand by secondary flows. Overestimating the transverse bed slope effect in morphodynamic models leadsto flattening of the morphology, while underestimating leads to unrealistically steep bars and banks and ahigher braiding index downstream. However, existing transverse bed slope predictors are based on a smallset of experiments with a minor range of flow conditions and sediment sizes, and in practice models are calibratedon measured morphology. The objective of this research is to experimentally quantify the transversebed slope effect for a large range of near-bed flow conditions with varying secondary flow intensity, sedimentsizes (0.17–4 mm), sediment transport mode, and bed state to test existing predictors. We conductedover 200 experiments in a rotating annular flume with counterrotating floor, which allows control of the secondaryflow intensity separate from the streamwise flow velocity. Flow velocity vectors were determinedwith a calibrated analytical model accounting for rough bed conditions. We isolated separate effects of allimportant parameters on the transverse slope. Resulting equilibrium transverse slopes show a clear trendwith varying sediment mobilities and secondary flow intensities that deviate from known predictorsdepending on Shields number, and strongly depend on bed state and sediment transport mode. Fittedfunctions are provided for application in morphodynamic modeling |
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