Degree

Doctor of Philosophy (PhD)

Department

Civil and Environmental

Document Type

Dissertation

Abstract

Land loss restoration along the southeast Louisiana coast relies on the replenishment of sand from the sediment of the Mississippi River. To further the understanding of sediment transport and hydraulic characteristics of the lowermost segment of the river, the Louisiana Coastal Protection and Restoration Authority (CPRA) funded construction of the Lower Mississippi River Physical Model (LMRPM). This distorted-scale, movable bed model encompasses the lowermost 193-mile reach of the river, including from Donaldsonville, Louisiana to the Gulf of Mexico the Bonnet Carre Spillway and planned river sediment diversions.

Designed to replicate the prototypical river hydraulics and bulk bedload (sand) transport, scaled historic river discharges are routed through the model.. Lightweight synthetic particles representing the very fine to fine grain sand sediments of the lower river are injected based on the results of a numerical sediment transport simulation from Tarbert Landing to the Gulf of Mexico. The depths and opaqueness of the model make it challenging to non-destructively measure real-time sediment transport. The objective of the research is employ non-destructive methods to measure reach-by-reach sediment levels that can be used to predict the scour and deposition of the bed load sediments. Having a method to locate and quantity sediment accumulations would benefit both navigational and coastal restoration stakeholders. During a LMRPM test of 1995 through 1999 discharges, ultrasonic sensors measured the sediment bed levels along a 17-mile reach of the model. Measured year-to-year bed elevation changes were translated into volumetric changes and compared to computed bed volume changes using boundary shear stress results from 1-D, unsteady flow numerical simulations. The measured-to-observed data, plotted in a scatter graph, align closely to 1:1 regression line of observed-to-observed values validating the process. This approach was also shown to successfully predict deposition patterns in one of the prototype lowermost river crossings.

Date

4-11-2022

Committee Chair

Willson, Clinton S.

DOI

10.31390/gradschool_dissertations.5810

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