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SEDTRANS96: the upgraded and better calibrated sediment-transport model for continental shelves

Li, M.Z. and Amos, C.L. (2001) SEDTRANS96: the upgraded and better calibrated sediment-transport model for continental shelves Computers and Geoscience, 27, pp. 619-645. (doi:10.1016/S0098-3004(00)00120-5).

Record type: Article


The sediment transport model SEDTRANS has been significantly upgraded based on new advances in both cohesive and non-cohesive sediment transport studies. For given input data of wave, current, and seabed conditions, the model applies the combined wave–current bottom boundary layer theories to derive the near-bed velocity profile and bed shear stresses, and then calculates sediment transport for currents only or combined waves and currents over either cohesive or non-cohesive sediments. Critical shear stresses for various sediment transport modes tested for combined waves and currents are adopted in SEDTRANS96. An explicit combined-flow ripple predictor is included in the model to provide time-dependent bed roughness prediction. SEDTRANS96 also predicts the vertical profiles of velocity and suspended sediment concentration and their product is integrated through depth to derive the suspended-load transport rate. More rigorous calibration of the model using measured sediment transport rates over fine and medium sands shows that the difference between the predicted and measured transport rates has been reduced from more than one order of magnitude to less than a factor of five. The proposed new cohesive sediment algorithm separates cohesive sediment transport into depositional, stable and erosional states. The applied shear stress, erosion/deposition time duration and the down-core profile of the critical shear stress for erosion are numerically integrated to predict the final erosion or deposition rate, suspension concentration and transport rate for cohesive sediment.

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Published date: 2001
Keywords: Current or combined wave–current flows, Cohesive or non-cohesive sediment transport, Computer simulation, Model prediction and field data


Local EPrints ID: 12576
PURE UUID: ecd9c88b-b003-470b-b7fe-65112714d55d

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Date deposited: 25 Nov 2004
Last modified: 17 Jul 2017 17:02

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Author: M.Z. Li
Author: C.L. Amos

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