Changes in ripple migration rates and hydraulic resistance with increasing mud-to-sand ratios

Fernandez, Roberto, Kassem, Hachem, Wu, Xuxu and Parsons, Daniel (2022) Changes in ripple migration rates and hydraulic resistance with increasing mud-to-sand ratios. In Proceedings of the 39th IAHR World Congress (Granada, 2022). International Association for Hydro-Environment Engineering and Research.. (doi:10.3850/IAHR-39WC2521711920221870).

Abstract

Coasts, estuaries, and lowland river environments are some of the most sensitive systems to climate-induced environmental change. In order to manage these systems, and adapt to future changes, we need to be able to predict how they might change. However, most available models have formulations based on assumptions that these systems are composed of only non-cohesive sands, even if mud is the most common sediment on Earth. Therefore, we need to find ways to incorporate the effect of sticky mud in predictors of flow resistance, sediment transport rates, and bedform geometries associated with form drag. In this paper, we show results from seven experiments conducted with different mud contents (0% - 12.6%) under the combined action of waves and currents. Experiments were conducted over a time period that was greater than the time needed for the bedform ripples to be at equilibrium with the imposed flow conditions. Our results reveal a mud content threshold above which friction coefficients are 4-6 times smaller than for clean sand and lower mud content counterparts. Below this threshold, flow resistance decreases with increasing mud content even though ripple migration rates are similar. Near the threshold, ripple migration rates increase as shorter ripples form and travel faster; the associated bedload transport rates also increase near the threshold and decrease beyond it. The threshold mud content, likely to vary with substrate composition and hydrodynamic conditions, is key to better estimating the behavior of different systems and needs further studies to properly incorporate it into predictors.

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Contributors

Author: Hachem Kassem

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