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ARS Home » Southeast Area » Oxford, Mississippi » National Sedimentation Laboratory » Watershed Physical Processes Research » Research » Publications at this Location » Publication #394568

Research Project: Computational Tools and a Decision Support System for Management of Sediment and Water Quality in Agricultural Watersheds

Location: Watershed Physical Processes Research

Title: Three-dimensional numerical modeling of flow hydrodynamics and cohesive sediment transport in Enid Lake, Mississippi

Author
item CHAO, XIAOBO - University Of Mississippi
item HOSSAIN, AZAD - University Of Tennessee
item AL-HAMDAN, MOHAMMAD - University Of Mississippi
item JIA, YAFEI - University Of Mississippi
item CIZDZIEL, JAMES - University Of Mississippi

Submitted to: Geosciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/30/2022
Publication Date: 4/2/2022
Citation: Chao, X., Hossain, A., Al-Hamdan, M., Jia, Y., Cizdziel, J. 2022. Three-dimensional numerical modeling of flow hydrodynamics and cohesive sediment transport in Enid Lake, Mississippi. Geosciences. 12(4):160. https://doi.org/10.3390/geosciences12040160.
DOI: https://doi.org/10.3390/geosciences12040160

Interpretive Summary: A three dimensional (3D) numerical model has been developed to predict the dynamic flow fields, and the temporal and spatial concentrations of cohesive sediment in the entire lake. Based on the upstream river flow discharge, sediment concentration, outlet water surface elevation, and wind conditions, the flow fields, including velocity, water level, eddy viscosity, and the concentration of cohesive sediment in the lake can be solved. In the model, the general processes of cohesive sediment transport, including flocculation, settling, deposition and erosion were considered. The developed model was calibrated using the field measured data, and then it was applied to simulate a spring storm event in Enid Lake. The simulated cohesive sediment concentration was generally in agreement with satellite imagery. Model results and satellite imagery show that the concentration of sediment was higher near the river mouth and shallow shoreline area than that in the deeper water areas near the dam. Remote sensing technology has been successfully used to estimate and map the distributions of suspended sediments (SS) at the entire lake surface following a storm event. It also provided useful information for numerical model validation. The results from this study are directly applicable to other large lake systems in Mississippi and elsewhere. Remote sensing and numerical model are both useful tools for estimation and mapping sediment concentration in large lakes. This research demonstrates the advantages for sediment studies in large water-bodies by integrating the numerical model and remote sensing data: remote sensing can provide initial condition and validation data for numerical model; numerical model can simulate the spatial and temporal distributions of sediment concentration for the entire waterbody, which may provide useful information to estimate the missing remote sensing data and map the SS distributions under the water surface.

Technical Abstract: Enid Lake is one of the largest reservoirs located in Yazoo River Basin, the largest basin in the state of Mississippi. The lake was impounded by Enid Dam on the Yocona River in Yalobusha County and covers an area of 30 square kilometers. It provides significant natural and recreational resources. The soils in this region are highly erodible, resulting in a large amount of fine-grained cohesive sediment discharged into the lake. In this study, a 3D numerical model was developed to simulate the free surface hydrodynamics and transportations of cohesive sediment with median diameter of 0.0025 to 0.003 mm in Enid Lake. Flow fields in the lake are generally induced by wind and upstream river inflow, and the sediment is also introduced from the inflow during the storm evens. The general processes of sediment flocculation and settling were considered in the model, and the erosion rate and deposition rate of cohesive sediment were calculated. In this model, the sediment simulation was coupled with flow simulation. In this research, remote sensing technology was applied to estimate the sediment concentration at the lake surface and provide validation data for numerical model simulation. The model results and remote sensing data help us understand the transport, deposition and resuspension processes of cohesive sediment in large reservoir due to wind-induced current and upstream river flow.