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Abstract
Turbidity currents, which are stratified, sediment-laden bottom flows in the ocean or lakes, can run out for 100's to 1000's of kilometers in submarine channels without losing their stratified structure. Here we derive a layer-averaged, two-layer model for turbidity currents, specifically designed to capture long-runout. Previous models have captured runout only 10’s of kilometers, beyond which thickening of the flows becomes excessive and the models without a lateral overspill mechanism fail. In our framework, a lower layer containing nearly all the sediment is a faster, gravity-driven flow that propels an upper layer, where sediment concentration is nearly zero. The thickness of the lower layer is controlled by a competition between interfacial water entrainment due to turbulent mixing and water detrainment due to sediment settling at the interface. The detrainment mechanism, first identified in experiments, is the key feature that prevents excessive thickening of the lower layer and allows long-runout. Under normal flow conditions, we obtain an exact solution to the two-layer formulation revealing a constant velocity and a constant thickening rate in each of the two layers. Numerical simulations applied to gradually varied flows on both constant and exponentially declining bed slopes, with boundary conditions mimicking field observations, show that the predicted lower layer thickness after 200-km flow propagation compares with observed submarine channel depths, whereas previous models overestimate this thickness by 3-4 fold. This formulation opens new avenues for modeling the fluid mechanics and morphodynamics of long-runout turbidity currents in the submarine setting.
DOI
https://doi.org/10.31223/X5M41R
Subjects
Engineering, Physical Sciences and Mathematics
Keywords
Turbidity Current; Long-runout; Sediment-laden Flow; Stratified Flow; Morphodynamics
Dates
Published: 2024-08-28 23:07
Last Updated: 2024-08-29 06:07
License
CC-By Attribution-NonCommercial-NoDerivatives 4.0 International
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Conflict of interest statement:
None
Data Availability (Reason not available):
The data/code that support the findings of this study are available from the corresponding author upon reasonable request.
There are no comments or no comments have been made public for this article.