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Structured Decision Making in Barrier Island Restoration

Study demonstrates the potential for informing management decisions and guiding the focus of scientific research.

This article is part of the October-December 2016 issue of the Sound Waves newsletter.

Imagery of a coastal area showing land, islands, and ocean, with labels.
Map showing the location of Ship Island, Mississippi. The focus of the study is the planned restoration of Ship Island, Mississippi, a once-contiguous barrier island in the northern Gulf of Mexico that has been split in two since Hurricane Camille (1967).

A new study, “Use of structured decision-making to explicitly incorporate environmental process understanding in management of coastal restoration projects: Case study on barrier islands of the northern Gulf of Mexico,” demonstrates the use of a decision-analysis tool to inform management of coastal restoration projects and identify high-priority research gaps.

The focus of the study is the planned restoration of Ship Island, Mississippi, a once-contiguous barrier island in the northern Gulf of Mexico that has been split in two since Hurricane Camille (1967). As part of the Mississippi Coastal Improvements Program, the U.S. Army Corps of Engineers plans to use approximately 22 million cubic yards of sand to close the gap between East and West Ship Islands and nourish the eastern end to enhance the supply of sand via longshore transport.

The project will take place in five phases over approximately three years. If a tropical storm occurs during construction and damages the project, management decisions will have to be made regarding if and when (i.e., which construction phase) repairs should be made to maximize the likelihood that the project will achieve its objectives of habitat restoration and protecting the mainland from waves. 

In this study, structured decision-making (SDM) was evaluated as a tool for incorporating data and environmental process knowledge directly into coastal restoration management decisions. The transparent SDM process included soliciting input from stakeholders on project objectives and relative importance, and from scientists and engineers on the physical drivers and response of the system. This input was incorporated into a probabilistic framework that linked storm inundation data, the physical response of the island, repair decisions, and sand and budget constraints to the quantitative impacts on project objectives. If the project incurs damage during construction, this framework will be used to inform decisions made in response. For example, the analysis indicated that it is more cost effective to repair major damage immediately despite the additional cost of moving equipment, rather than wait until a subsequent construction phase and risk additional damage to the weakened project.

Flow chart shows the various influences of storms on islands and the process to decide whether or not to repair a breach.
Example of a simplified influence diagram developed in building a structured decision-making framework at Ship Island, in this case representing a single decision on whether or not to repair a major breach in Phase B2. Influence diagrams conceptually link system drivers and response, budget and sand constraints, management decisions, and the objectives of the project. A Bayesian (probabilistic) network was developed to statistically evaluate the quantitative impact of possible damage and response decisions on project objectives.

In addition to providing a framework for analyzing decisions at Ship Island, this effort identified several key gaps in scientific understanding of barrier island dynamics that limit the ability to robustly manage coastal restoration projects. For example, there is relatively high uncertainty in predicting the relation between island width and storm resilience, and in quantifying the potential benefits of upstream sand nourishment on project longevity.  

This study demonstrates the potential for structured decision-making to directly incorporate scientific and engineering knowledge into a framework that can both improve coastal restoration management and identify priority gaps in data, predicting model capability, and process understanding that can be filled with targeted scientific research.

This effort included collaborators from the USGS, U.S. Army Corps of Engineers, University of Natural Resources and Life Sciences Institute of Silviculture, Applied Coastal Research and Engineering, the National Park Service, and the Louisiana Coastal Protection and Restoration Authority. Funding was provided by the Department of the Interior Southeast Climate Science Center.

The full citation for the article is:

Dalyander, P.S., Meyers, M., Mattsson, B.J., Steyer, G., Godsey, E., McDonald, J., Byrnes, M., and Ford, M., 2016, Use of structured decision-making to explicitly incorporate environment process understanding in management of coastal restoration projects:  Case study on barrier islands of the northern Gulf of Mexico:  Journal of Environmental Management, doi: 10.1016/j.jenvman.2016.08.078.

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