1 

Technical Summary (NSL GM-14-03-10)

Study Title Assessment of Ship Shoal Borrow Areas for Coastal Restoration of Louisiana 

Barrier Islands

Report Title Assessment of Ship Shoal borrow areas for coastal restoration of Louisiana 

barrier islands

Report Number(s) (OCS 

Study) 2024-058

Completion Date of Report 9/1/2024

Number of Pages 40 

Award Number(s) M16AC00018

Sponsoring OCS Region or 

Office Gulf of Mexico

Applicable Planning Area(s) Central and Western Planning Areas

Fiscal Year(s) of Study 

Funding FY16–FY24

Costs by Fiscal Year $92,997.00 in Year 1; $192,157.00 in Year 2; $106,623.00 in Year 3;

Cumulative Project Cost $391,777.00

Project Manager(s) Dr. Kehui Xu

Affiliation of Project 

Manager(s) Louisiana State University

Address of Project 

Manager(s) 2165 Energy, Coast, and Environment Building, Baton Rouge, LA, 70803

Principal Investigator(s) Dr. Kehui Xu

Keywords dredge pit, geomorphology, bathymetry, dredging, Mississippi River Delta Plain, 

sediment borrow areas, Louisiana shelf

ABSTRACT: 

A geological and physical oceanographic study of Caminada and Block 88 borrow areas on Ship Shoal in 

the inner Louisiana shelf was conducted using comprehensive approaches of geophysical surveys, 

coring, field observation, and data synthesis. Data collected in Ship Shoal borrow areas were used to 

assess present pit morphology. Existing data from mud-capped pits and newly acquired data from sandy 

pits were compared and analyzed, and employed to validate numerical models. The study built on 

BOEM’s investment toward better understanding sandy shoal dredge pit problem by filling data gaps 

and validating predictive models and focused on evaluating the effectiveness of mitigations applied to 

existing sandy dredge pits. 

BACKGROUND: 

Several previous studies have informed BOEM decisions about dredging setback distances from 

pipelines and potential cultural resources. Of particular concern was that the long-term evolution of 
2 

dredge pits would compromise the required three feet of sediment cover over pipelines. The models 

predicted that pit filling would be rapid and so there should not be concern about long term evolution 

and impacts to infrastructure, cultural resources, water quality, or habitat. Until now there had been no 

opportunity to verify these predictions. The active dredging projects for Caminada that ended in the

summer of 2016 and for Ship Shoal Block 88 at the end of 2017 provided a unique opportunity to test 

model predictions and effectiveness of assigned mitigations, monitor borrow area geomorphic 

evolution, develop monitoring protocols, and refine predicative capability for future projects. 

OBJECTIVES: 

This project leveraged resources from previous projects and expanded upon the effects that physical 

changes may have on hydrodynamics, geomorphology, and sediment transport processes at Caminada 

and Block 88 dredge pits on Ship Shoal. The primary goal of this study was to observe the early stages of 

post dredging impacts on sediment transport and geomorphology. We validated the model of previous 

studies with newly collected data, identified the type and quality of filling-in sediment and quantify 

sediment accumulation rates, assessed the effectiveness of existing mitigations, and provided 

recommendations for pit monitoring protocols.

METHODS: 

There were two main study areas in this project: inside and outside of Block 88 dredge pit and inside and 

outside of Caminada dredge pit. Major methods included vessel-based acoustic doppler current profiler 

(ADCP), coring and geophysical surveys (bathymetry, subbottom, and sidescan). 

RESULTS: 

This study found that the infilling of the Caminada and Block 88 dredge pits is not primarily composed of 

ambient Ship Shoal sand, as had been hypothesized. Instead, analysis reveals a significant absence of 

sand within the infilled material in the interior of the dredge pit. Findings from this study indicate that 

the infill is mainly of fine to medium silts, occasionally interspersed with laminations of coarser silt and 

sparse very fine sand laminations. Through the presence of sediments containing 7Be and grain size 

analysis of cores extracted from two pits, it was determined that the infill is sourced from a combination 

of the Atchafalaya and Mississippi River plumes. In addition, it is suggested that storm events may 

resuspend fine-grained material from the shelf and local bays, transporting it to the dredge pit. 

Furthermore, the infilling at Caminada and Block 88 dredge pits was at a slower rate (~5 times less) than 

numerical modeling predicted in previous studies. It was also slower than several mud-capped dredge 

pits in Louisiana. 

CONCLUSIONS: 

Our results in Block 88 pit suggest that future dredge pits can be designed to capitalize on the 

environmental conditions at Ship Shoal, promoting sediment capture. The choice of dredging equipment 

shapes the bottom morphology of the pit, which in turn influences the distribution of sediment 

accumulation within the pit. The recent dredging projects at Block 88 and Caminada pits offer valuable 

insights into how the location, geometry, and type of borrow area influence the infilling sediment type 

and rate. The infilling at Block 88 pit highlights that the pit orientation relative to longshore transport is 

a key factor in successfully trapping larger grain sizes (sands), while the microtopography of the pit 

bottom dictates the trapping of finer grain sizes (muds). Future pits excavated at Ship Shoal and similar 

shallow submarine shoals in the Northern Gulf of Mexico should have their long axis perpendicular to 
3 

the longshore sediment transport direction to maximize natural trapping of bed load. This approach 

could lead to increased interception, trapping, and potential reuse of bed load and sand. The past 

modeling work for Block 88 overestimated the sediment infilling rate, suggesting that future models 

should be improved to assess whether the dredge pit dimensions or the model type need reassessment. 

It is crucial that both suspended load and bed load are explicitly modeled, as this study demonstrates 

that the sediment accumulation rate and the gross sediment transport rate assumed for Ship Shoal were 

too high. These findings will enhance decision-making regarding seafloor stability and the protection of 

environmental and cultural resources, while also providing valuable datasets for better management of 

limited sand resources. 

STUDY PRODUCT(S):

Report: Xu K, Bentley S, Li C, Wilson C, Liu H, Lopez G, Moran K, Wu Z. 2024. Assessment of Ship Shoal 

Borrow Areas for coastal restoration of Louisiana barrier islands. New Orleans (LA): US Department 

of the Interior, Bureau of Ocean Energy Management. Obligation No.: M16AC00018. Report No.: 

BOEM 2024-xxx. 40 p.

Moran K, Xu KH, Wilson C, Lopez G. 2022. Contrasting modes of sediment infilling and geomorphic 

change within a sand dominated dredge pit on the inner Louisiana shelf. Estuar Coast Shelf Sci. 

278:108127.

Liu H, Xu K, Wilson C, et al. 2022. Geomorphologic change and patchy mud infilling in a sandy dredge pit 

in eastern Ship Shoal, Louisiana shelf, USA. Geomorphology. 396:107983.

Xue Z, Wilson CA, Xu KH, et al. 2022. Sandy borrow area sedimentation-characteristics and processes 

within South Pelto dredge pit on Ship Shoal, Louisiana shelf, USA. Estuar Coast. 1-19.

Liu H, Xu K, Ou Y, et al. 2020. Sediment transport near Ship Shoal for coastal restoration in the Louisiana

shelf: A model estimate of the year 2017–2018. Water. 12(8):2212.

Liu H, Xu K, Li B, et al. 2019. Sediment identification using machine learning classifiers in a mixed-texture 

dredge pit of Louisiana shelf for coastal restoration. Water. 11:1257.

MAP OF STUDY AREA:

Figure 1. Base map. 
4 

Map showing the locations of two dredge pits at Caminada and Block 88 in Ship Shoal area, and Raccoon 

Island borrow area. Black dots are Louisiana State University WAVCIS (wave-current information 

system) stations at CSI5 and CSI6. The background color contours are bathymetry from ETOPO1 Global 

Relief Model (https://www.ncei.noaa.gov/access/metadata/landingpage/bin/iso?id=gov.noaa.ngdc.mgg.dem:316).