Abstract

The Louisiana barrier islands are one of the outcomes of the Mississippi River outlet changing over the past several thousand years. It is the natural shifts in the river channel alignment interacting with the combination of anthropogenic impacts, sediment transport, and significant storm events that drive barrier island formation and subsequent erosion and migration. Predicting the evolution of Louisiana’s barrier islands is a critical component of Louisiana’s Coastal Protection and Restoration Authority (CPRA) program for restoring and sustaining their barrier islands. Both empirical and numerical modeling approaches, as well as hybrid modeling approaches, have been utilized for predicting morphologic changes over time. These predictions have been employed for the development of single-island restoration projects, and for the long-term basin-scale modeling completed for the 2017 Coastal Master Plan (CPRA, 2017) for which Coastal Engineering Consultants served on the barrier island modeling team.

Highlights

  • The Louisiana barrier islands are one of the outcomes of the Mississippi River outlet changing over the past several thousand years

  • CASE STUDIES The process-based modeling approach utilized by Coastal Engineering Consultants for the design of a systemwide multi-island restoration project (Figure 1) and the hybrid modeling approach employed for the 2017 Coastal Master Plan will be presented

  • LONGSHORE TRANSPORT Longshore transport is defined as the movement of sediment parallel to the shoreline caused by waves approaching the shoreline obliquely and/or longshore currents

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Summary

Introduction

The Louisiana barrier islands are one of the outcomes of the Mississippi River outlet changing over the past several thousand years. Model (Booij et al, 1996) calibrated to published longshore transport rates and the CERC transport formulation were employed. For cross-shore transport, SBEACH was utilized to develop look up tables to represent the range of possible profile responses to select storms (CPRA, 2017).

Results
Conclusion

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