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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Developing Sediment Transport and Deposition Prediction Model of Lower Ohio River near the Olmsted Locks and Dam Area

Ghimire, Ganesh Raj 01 August 2016 (has links)
The present study focuses on the sediment deposition and consequent dredging issues in Lower Ohio River at the Olmsted Locks and Dam area-River mile (RM)-964.4 during the ongoing in-the-wet construction methodology. The study reach is between Locks and Dam 53 (RM 962.6) at upstream, and RM 970 at downstream. One dimensional (1-D) HEC-RAS numerical modeling in conjunction with Arc-GIS was employed. Stream flow measurements, velocity, incoming sediment concentration, bed gradation, and annual hydrographic survey data acquired from public archives of USGS and USACE Louisville District were used as inputs. The model was subjected to the 1-D quasi-unsteady and completely unsteady sediment transport module, available in the latest HEC-RAS 5.0 Beta release. Calibration and validation of the hydrodynamic and sediment models were performed using measured water surface elevation, velocity, and sediment loads at measured sections. Post-model calibration and validation, deposition to excavated cross-sections for future dam shells at Olmsted was predicted, which warrants dredging. The study attempted to analyze the sediment transport trend with the focus on depositionat Olmsted Locks and Dam area using the sensitivity analysis approach of transport capacity functions. Moreover, the capability of 1-D HEC-RAS quasi-unsteady and completely unsteady models were assessed in prediction of sediment deposition in the construction area (dam shells excavation area). A temporal deposition prediction model was developed that can potentially replace the current ad-hoc approach used to determine the dredging schedule. Likewise, a representative environmental risk associated with sedimentation in the study area was examined. The model can potentially be used as a decision support tool to analyze the long term impact of sedimentation in the vicinity of Olmsted Locks and Dam if further updates on the river bathymetry, and specific field data are supplemented to the model.

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