Turbidity currents, and other types of submarine sediment density flow, redistribute more sediment across the surface of the Earth than any other sediment flow process, yet their sediment concentration has never been measured directly in the deep ocean. The deposits of these flows are of societal importance as imperfect records of past earthquakes and tsunamogenic landslides and as the reservoir rocks for many deep-water petroleum accumulations. Key future research directions on these flows and their deposits were identified at an informal workshop in September 2013. This contribution summarizes conclusions from that workshop, and engages the wider community in this debate. International efforts are needed for an initiative to monitor and understand a series of test sites where flows occur frequently, which needs coordination to optimize sharing of equipment and interpretation of data. Direct monitoring observations should be combined with cores and seismic data to link flow and deposit character, whilst experimental and numerical models play a key role in understanding field observations. Such an initiative may be timely and feasible, due to recent technological advances in monitoring sensors, moorings, and autonomous data recovery. This is illustrated here by recently collected data from the Squamish River delta, Monterey Canyon, Congo Canyon, and offshore SE Taiwan. A series of other key topics are then highlighted. Theoretical considerations suggest that supercritical flows may often occur on gradients of greater than , 0.6u. Trains of up-slope-migrating bedforms have recently been mapped in a wide range of marine and freshwater settings. They may result from repeated hydraulic jumps in supercritical flows, and dense (greater than approximately 10% volume) near-bed layers may need to be invoked to explain transport of heavy (25 to 1,000 kg) blocks. Future work needs to understand how sediment is transported in these bedforms, the internal structure and preservation potential of their deposits, and their use in facies prediction. Turbulence damping may be widespread and commonplace in submarine sediment density flows, particularly as flows decelerate, because it can occur at low (, 0.1%) volume concentrations. This could have important implications for flow evolution and deposit geometries. Better quantitative constraints are needed on what controls flow capacity and competence, together with improved constraints on bed erosion and sediment resuspension. Recent advances in understanding dilute or mainly saline flows in submarine channels should be extended to explore how flow behavior changes as sediment concentrations increase. The petroleum industry requires predictive models of longer-term channel system behavior and resulting deposit architecture, and for these purposes it is important to distinguish between geomorphic and stratigraphic surfaces

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Abstract. Turbidity currents are one of the main drivers of sediment transport from the continental shelf to the deep ocean. The resulting sediment deposits can reach hundreds of kilometres into the ocean. Computer models that simulate turbidity currents and the resulting sediment deposit can help us to understand their general behaviour. However, in order to recreate real-world scenarios, the challenge is to find the turbidity current parameters that reproduce the observations of sediment deposits. This paper demonstrates a solution to the inverse sediment transportation problem: for a known sedimentary deposit, the developed model reconstructs details about the turbidity current that produced the deposit. The reconstruction is constrained here by a shallow water sediment-laden density current model, which is discretised by the finite-element method and an adaptive time-stepping scheme. The model is differentiated using the adjoint approach, and an efficient gradientbased optimisation method is applied to identify the turbidity parameters which minimise the misfit between the modelled and the observed field sediment deposits. The capabilities of this approach are demonstrated using measurements taken in the Miocene Marnoso-arenacea Formation (Italy). We find that whilst the model cannot match the deposit exactly due to limitations in the physical processes simulated, it provides valuable insights into the depositional processes and represents a significant advance in our toolset for interpreting turbidity current deposits.

Abstract. High resolution direct numerical simulations (DNS) are an important tool for the detailed analysis of turbidity current dynamics. Models that resolve the vertical structure and turbulence of the flow are typically based upon the Navier–Stokes equations. Two-dimensional simulations are known to produce unrealistic cohesive vortices that are not representative of the real three-dimensional physics. The effect of this phenomena is particularly apparent in the later stages of flow propagation. The ideal solution to this problem is to run the simulation in three dimensions but this is computationally expensive. This paper presents a novel finite-element (FE) DNS turbidity current model that has been built within Fluidity, an open source, general purpose, computational fluid dynamics code. The model is validated through re-creation of a lock release density current at a Grashof number of 5 × 106 in two, and three-dimensions. Validation of the model considers the flow energy budget, sedimentation rate, head speed, wall normal velocity profiles and the final deposit. Conservation of energy in particular is found to be a good metric for measuring mesh performance in capturing the range of dynamics. FE models scale well over many thousands of processors and do not impose restrictions on domain shape, but they are computationally expensive. Use of discontinuous discretisations and adaptive unstructured meshing technologies, which reduce the required element count by approximately two orders of magnitude, results in high resolution DNS models of turbidity currents at a fraction of the cost of traditional FE models. The benefits of this technique will enable simulation of turbidity currents in complex and large domains where DNS modelling was previously unachievable.

Abstract. High-resolution direct numerical simulations (DNSs) are an important tool for the detailed analysis of turbidity current dynamics. Models that resolve the vertical structure and turbulence of the flow are typically based upon the Navier-Stokes equations. Two-dimensional simulations are known to produce unrealistic cohesive vortices that are not representative of the real three-dimensional physics. The effect of this phenomena is particularly apparent in the later stages of flow propagation. The ideal solution to this problem is to run the simulation in three dimensions but this is computationally expensive. This paper presents a novel finite-element (FE) DNS turbidity current model that has been built within Fluidity, an open source, general purpose, computational fluid dynamics code. The model is validated through re-creation of a lock release density current at a Grashof number of 5 × 10 6 in two and three dimensions. Validation of the model considers the flow energy budget, sedimentation rate, head speed, wall normal velocity profiles and the final deposit. Conservation of energy in particular is found to be a good metric for measuring model performance in capturing the range of dynamics on a range of meshes. FE models scale well over many thousands of processors and do not impose restrictions on domain shape, but they are computationally expensive. The use of adaptive mesh optimisation is shown to reduce the required element count by approximately two orders of magnitude in comparison with fixed, uniform mesh simulations. This leads to a substantial reduction in computational cost. The computational savings and flexibility afforded by adaptivity along with the flexibility of FE methods make this model well suited to simulating turbidity currents in complex domains.

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Abstract. Turbidity currents are one of the main drivers for sediment transport from the continental shelf to the deep ocean. The resulting sediment deposits can reach hundreds of kilometres into the ocean. Computer models that simulate turbidity currents and the resulting sediment deposit can help to understand their general behaviour. However, in order to recreate real-world scenarios, the challenge is to find the turbidity current parameters that reproduce the observations of sediment deposits. This paper demonstrates a solution to the inverse sediment transportation problem: for a known sedimentary deposit, the developed model reconstructs details about the turbidity current that produced these deposits. The reconstruction is constrained here by a shallow water sediment-laden density current model, which is discretised by the finite element method and an adaptive time-stepping scheme. The model is differentiated using the adjoint approach and an efficient gradient-based optimisation method is applied to identify turbidity parameters which minimise the misfit between modelled and observed field sediment deposits. The capabilities of this approach are demonstrated using measurements taken in the Miocene-age Marnoso Arenacea Formation (Italy). We find that whilst the model cannot match the deposit exactly due to limitations in the physical processes simulated, it provides valuable insights into the depositional processes and represents a significant advance in our toolset for interpreting turbidity current deposits.