The sensitivity of turbidity currents to mass and momentum exchanges between these underflows and their surroundings

Traer, M. M.; Hilley, G. E.; Fildani, Andrea; McHargue, T.

doi:10.1029/2011jf001990

Cited by 26 publications

(26 citation statements)

References 52 publications

(96 reference statements)

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“…Traer et al . [] have also pointed out the sensitivity of turbidity current dynamics to choices regarding the erosion (or sediment entrainment) law, albeit with u ∗ linked to the turbulence via equation , which is not our model here. Fortunately, as will be seen below, while Z C is important in demarcating the boundary of the region of possible steady‐state flow, it does not affect the values of physical parameters such as concentration C within the region of steady‐state flow.…”

Section: Depth‐averaged Model For Turbidity Currentsmentioning

confidence: 99%

Sedimentological regimes for turbidity currents: Depth‐averaged theory

2017

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Turbidity currents are one of the most significant means by which sediment is moved from the continents into the deep ocean; their properties are interesting both as elements of the global sediment cycle and due to their role in contributing to the formation of deep water oil and gas reservoirs. One of the simplest models of the dynamics of turbidity current flow was introduced three decades ago, and is based on depth‐averaging of the fluid mechanical equations governing the turbulent gravity‐driven flow of relatively dilute turbidity currents. We examine the sedimentological regimes of a simplified version of this model, focusing on the role of the Richardson number Ri [dimensionless inertia] and Rouse number Ro [dimensionless sedimentation velocity] in determining whether a current is net depositional or net erosional. We find that for large Rouse numbers, the currents are strongly net depositional due to the disappearance of local equilibria between erosion and deposition. At lower Rouse numbers, the Richardson number also plays a role in determining the degree of erosion versus deposition. The currents become more erosive at lower values of the product Ro × Ri, due to the effect of clear water entrainment. At higher values of this product, the turbulence becomes insufficient to maintain the sediment in suspension, as first pointed out by Knapp and Bagnold. We speculate on the potential for two‐layer solutions in this insufficiently turbulent regime, which would comprise substantial bedload flow with an overlying turbidity current.

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Section: Depth‐averaged Model For Turbidity Currentsmentioning

confidence: 99%

Sedimentological regimes for turbidity currents: Depth‐averaged theory

2017

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“…There are two groups of numerical models: depth‐resolving models [ Strauss and Glinsky , ; Yeh et al , ] and layer‐averaged models, which include the three‐equation model (TEM) and its variants [ Fukushima et al , ; Parker et al , ; Zeng and Lowe , ; Choi , ; Imran et al , ; Bradford and Katopodes , ; Kostic and Parker , , ; de Luna et al , ; Toniolo , ; Hu and Cao , ; Kostic et al , ; Eke et al , ; Hu et al , ; Lai and Wu , ; Kostic , ; Elfimov and Khakzad , ] and the Four‐Equation‐Model (FEM) and its variants [ Fukushima et al , ; Parker et al , ; Salaheldin et al , ; Pratson et al , ; Das et al , ; Fildani et al , ; Kostic and Parker , ; Yi and Imran , ; Eke et al , ; Kostic , ; Tracer et al , ]. The FEM differs from the TEM in the way in which the bed shear velocity ( u ∗ ) is computed [ Fukushima et al , ; Parker et al , ]: while the TEM computes u ∗ from the drag exerted on the bed, roughly approximated by

TEM: u_{*}^{2} = C_{D} U^{2},

where C D >0 is the bed drag coefficient and U the layer‐averaged velocity of the sediment‐water mixture, the FEM computes u ∗ from the assumption that the bed shear stress is proportional to the layer‐averaged turbulent kinetic energy ( k ),

FEM: u_{*}^{2} = αk,

where α > 0 is the dimensionless proportionality constant.…”

Section: Introductionmentioning

confidence: 99%

Is it appropriate to model turbidity currents with the three‐equation model?

Pähtz

2015

JGR Earth Surface

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The three-equation model (TEM) was developed in the 1980s to model turbidity currents (TCs) and has been widely used ever since. However, its physical justification was questioned because self-accelerating TCs simulated with the steady TEM seemed to violate the turbulent kinetic energy balance. This violation was considered as a result of very strong sediment erosion that consumes more turbulent kinetic energy than is produced. To confine bed erosion and thus remedy this issue, the four-equation model (FEM) was introduced by assuming a proportionality between the bed shear stress and the turbulent kinetic energy. Here we analytically proof that self-accelerating TCs simulated with the original steady TEM actually never violate the turbulent kinetic energy balance, provided that the bed drag coefficient is not unrealistically low. We find that stronger bed erosion, surprisingly, leads to more production of turbulent kinetic energy due to conversion of potential energy of eroded material into kinetic energy of the current. Furthermore, we analytically show that, for asymptotically supercritical flow conditions, the original steady TEM always produces self-accelerating TCs if the upstream boundary conditions ("ignition" values) are chosen appropriately, while it never does so for asymptotically subcritical flow conditions. We numerically show that our novel method to obtain the ignition values even works for Richardson numbers very near to unity. Our study also includes a comparison of the TEM and FEM closures for the bed shear stress to simulation data of a coupled Large Eddy and Discrete Element Model of sediment transport in water, which suggests that the TEM closure might be more realistic than the FEM closure.

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“…Such substitution facilitates simulations that explore landscape response to such varying processes. For example, q p (equation ) can be substituted with a GTL that describes sediment transport by debris flows [e.g., Stock and Dietrich , ], turbidity currents [e.g., Traer et al , ], Martian granular flows [e.g., Shinbrot et al , ], or rainfall‐generated parcels of water (which can be viewed as discrete flows). Further, as demonstrated through the effect of

\overset{S}{true}

on the flow runout, the proposed framework can explicitly record upslope topographic and flow conditions and account for the impact of such nonlocal factors on the downslope flow dynamics (in the sense of Stark et al [], Furbish and Haff [], Foufoula‐Georgiou et al [], Tucker and Bradley [], and Falcini et al []), such that upslope flow orientation, for example, can affect erosion and deposition at downslope locations [e.g., Howard , ; Stock and Dietrich , , ].…”

Section: Discussionmentioning

confidence: 99%

A unified framework for modeling landscape evolution by discrete flows

Shelef

Hilley

2016

JGR Earth Surface

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Topographic features such as branched valley networks and undissected convex-up hillslopes are observed in disparate physical environments. In some cases, these features are formed by sediment transport processes that occur discretely in space and time, while in others, by transport processes that are uniformly distributed across the landscape. This paper presents an analytical framework that reconciles the basic attributes of such sediment transport processes with the topographic features that they form and casts those in terms that are likely common to different physical environments. In this framework, temporal changes in surface elevation reflect the frequency with which the landscape is traversed by geophysical flows generated discretely in time and space. This frequency depends on the distance to which flows travel downslope, which depends on the dynamics of individual flows, the lithologic and topographic properties of the underlying substrate, and the coevolution of topography, erosion, and the routing of flows over the topographic surface. To explore this framework, we postulate simple formulations for sediment transport and flow runout distance and demonstrate that the conditions for hillslope and channel network formation can be cast in terms of fundamental parameters such as distance from drainage divide and a friction-like coefficient that describes a flow's resistance to motion. The framework we propose is intentionally general, but the postulated formulas can be substituted with those that aim to describe a specific process and to capture variations in the size distribution of such flow events.

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The sensitivity of turbidity currents to mass and momentum exchanges between these underflows and their surroundings

Cited by 26 publications

References 52 publications

Sedimentological regimes for turbidity currents: Depth‐averaged theory

Sedimentological regimes for turbidity currents: Depth‐averaged theory

Is it appropriate to model turbidity currents with the three‐equation model?

A unified framework for modeling landscape evolution by discrete flows

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