Abstract
Background, aim, and scope
The Lower Mississippi River is a major transportation route for commercial goods and petroleum products produced and refined locally. Oil spills caused by vessel accidents and equipment failure at refineries are a serious threat to the drinking water supply of Southern Louisiana, as well as to the many natural, economic, and social resources supported by the river. Providing accurate trajectory modeling to contingency planners is critical to protecting the local environment. The majority of trajectory model results, assuming a uniform shoreline, show 60–70% of spilled oil can be retained. This study examines the impact of detailed shoreline mapping that captures spatial and temporal changes in shoreline type on oil spill trajectory modeling.
Materials and methods
Detailed shoreline maps based on recent remote sensing imagery were generated to identify spatial changes in shoreline. A hydrodynamic model of the 78 mile reach from Convent, Louisiana to West Pointe a la Hache was developed to obtain the stage levels and velocity fields of four river discharges. Based on river stage level, another layer was added to the shoreline maps, so that shoreline type was accurately represented at each river discharge, a feature not included in previous mapping. An oil spill trajectory model was then used to investigate the effect of implementing different re-floatation half-lives that correlate to the shoreline maps developed for this study at four river discharges.
Results
Detailed shoreline mapping showed the Lower Mississippi River has four major shoreline types each with different oil re-floatation half-lives: muddy clay, sand, low vegetation, and high vegetation. As flow rate changed, the shoreline spatial variability also changed, from 84% mud/sand and 16% vegetation at low flow rates to 4% mud and 96% vegetation at higher flow rates. At flow rates with large variability in shoreline type, the distribution of oil attached to the shore was significantly different from results of simulations that used a constant shoreline type and re-floatation half-life.
Discussion
At low flow rates, simulations with the detailed delineation of shoreline type predicted that ~30% of the oil would be beached/retained because the oil was able to travel further down the reach and interact with the shoreline in multiple locations. Simulations at the low flow rates with the existing shoreline mapping predicted approximately 65% of the oil would be retained as did all the simulations at the highest flow rates. At high flow rates, the oil interacted mostly with vegetation and results were very similar to those obtained with a single re-floatation half-life of 1 year. In addition to shoreline type, river geometry and the hydrodynamics were major factors influencing the distribution of oil along the river reach.
Conclusions
Shoreline re-floatation half-lives have a major impact on simulating the distribution of oil along the shore after a spill, especially in areas with a high variability of shoreline type as in the lower Mississippi River. Assigning the correct re-floatation half-life and retention capacity is only possible when shoreline types have been correctly identified. The maps developed for this study provided an important level of detail and incorporated the change in shoreline type with flow rate, resulting in more detailed trajectory modeling of the study reach.
Recommendations and perspectives
Shoreline maps should include as much detail about shoreline type as possible. When developing shoreline maps or environmental sensitivity assessments, the focus should include specific characteristics of the study area; using standardized maps or methods of assessment may leave out detail that could negatively impact modeling efforts. Finally, shoreline sensitivity to oiling is an important area of research that will benefit from an improved understanding of oil retention by vegetation.
This is a preview of subscription content, access via your institution.





References
Aslan A, Autin WJ (1999) Evolution of the Holocene Mississippi River floodplain, Ferriday, Louisiana. J Sediment Res 69(4):800–815
Atlas (2008) The Louisiana Statewide GIS. LSU CADGIS Research Laboratory, Baton Rouge, LA. http://atlas.lsu.edu
Beegle-Krause CJ (2001) General NOAA Oil Modeling Environment (GNOME): a new spill trajectory model. Proceedings: International. Oil Spill Conference 2001, March 26–29, 2001, St. Louis, MO. Mira Digital 2:865–871
Berger RC, Tate JN (2007) ADH manual. USACE ERDC, Vicksburg, MS, http://chl.erdc.usace.army.mil/software
Coulter L, Stow D, Hope A, O’Leary J, Turner D, Longmire P, Peterson S, Kaiser J (2000) Comparison of high spatial resolution imagery for efficient generation of GIS vegetation layers. Photogramm Eng Remote Sens 66(11):1329–1335
Fisher B, Bellman C, Ellis J (1997) The development of a spatio-temporal environmental sensitivity index using GIS. Reef Res 7(3/4)
Hofer T (2003) Tanker safety and coastal environment: prestige, Erika and what else? Environ Sci Pollut Res 10(1):1–5
Jensen JR, Halls JN, Michel J (1998) A systems approach to Environmental Sensitivity Index (ESI) mapping for oil spill contingency planning and response. Photogramm Eng Remote Sens 64(10):1003–1014
LDHH (2006) Louisiana surface drinking water system intake locations. Louisiana Department of Health and Hospitals, http://lagic.lsu.edu/loscoweb/
LDNR (2007) Louisiana crude oil refinery survey report, 2007 Survey. Sixteenth Edition. Louisiana Department of Natural Resources Technology Assessment Division. Refining, Alternative Energy & Power Systems Program. Baton Rouge, LA
LOSCO (2008) Environmental sensitivity mapping. Louisiana Oil Spill Coordinator’s Office, http://lagic.lsu.edu/loscoweb/
Meade RH (1995) Contaminants in the Mississippi River. U.S. Geological Survey Circular 1133. Reston, VA, http://pubs.water.usgs.gov/circ1133/
Michel J, Hayes MO (1999) Weathering patterns of oil residues eight years after the Exxon Valdez oil spill. Mar Pollut Bull 38(10):855–863
Michel J, Henry JR. CB, Thumm S (2002) Shoreline assessment and environmental impacts from the M/T Westchester Oil Spill in the Mississippi River. Spill Sci Tech Bull 7(3/4):155–161
Mille G, Munoz D, Jacquot F, Rivet L, Bertrand JC (1998) The Amoco Cadiz oil spill: evolution of petroleum hydrocarbons in the Ile Grande Salt Marshes (Brittany) after a 13-year period. Estuar Coast Shelf Sci 47:547–559
NOAA (2001) Oil and hazardous materials spill reports. National Oceanic and Atmospheric Administration. http://response.restoration.noaa.gov/
NOAA (2002a) Environmental sensitivity index guidelines version 3.0. NOAA Technical Memorandum NOS OR&R 11. Hazardous Materials Response Division, Office of Response and Restoration, NOAA Ocean Service, National Oceanic and Atmospheric Administration. Seattle, WA
NOAA (2002b) General NOAA Oil Modeling Environment (GNOME) User’s manual. NOAA ORR http://response.restoration.noaa.gov/
NOAA (2008) Louisiana ESI Data. National Oceanic and Atmospheric Administration, http://response.restoration.noaa.gov
NRC (2008) Statistics & incident summaries 2001 to 2007. National Response Center, http://www.nrc.uscg.mil
Owens E, Lee K (2003) Interaction of oil and mineral fines on shorelines: review and assessment. Mar Pollut Bull 47:397–405
Owens EH, McGuire B, Humphrey B (1994) Chedabucto Bay 1992, shoreline conditions survey. Long-term Fate of Bunker C oil from the ARROW Spill in Chedabucto Bay, Nova Scotia. EPS Report 5/SP/2, Environment Canada, Ottawa ON, 85 pp
Owens E, Taylor E, Humphrey B (2008) Interaction of oil and mineral fines on shorelines: review and assessment. Mar Pollut Bull 56:14–26
Populus J, Moreau F, Coquelet D, Xavier JP (1995) An assessment of environmental sensitivity to marine pollutions: solutions with remote sensing and Geographical Information Systems (GIS) J. Int J Remote Sens 16(1):3–15
Rathbun RE, Rostad CE (2004) Lateral mixing in the Mississippi River below the confluence with the Ohio River. Water Resour Res 40:W05207.1–W05207.12
Reed M, Gundlach E, Kanay T (1989) A coastal zone oil spill model: development and sensitivity studies. Oil Chem Pollut 5(6):411–449
Reed M, Johansen O, Brandvik PJ (1999) Oil spill modeling towards the close of the 20th century. Spill Sci Technol Bull 5(1):1–16
Torgrimson GM (1980) The On-Scene-Spill Model: a user's guide, technical report, hazardous mater. NOAA ORR, Seattle, Wash
Tortell P (1992) Coastal zone sensitivity mapping and its role in marine environmental management. Mar Pollut Bull 25:88–93
USACE (2008) New Orleans District Water Control Discharge Data. US Army Corps of Engineers http://www.mvn.usace.army.mil/
Waldon M (1998) Time-of-travel in the lower Mississippi River: model development, calibration, and application. Water Environ Res 70(6):1132–1141
Wang Z, Fingas M, Owens EH, Sigouin L (2000) Study of long-term spilled Metula oil: degradation and persistence of petroleum biomarkers. In: Proceedings of the 23rd Arctic and Marine Oilspill programme (AMOP) Technical Seminar, Environment Canada, Ottawa ON, pp 99–122.
Westerink J, Bunya S, Dietrich C, Luettich R, Ebersole B, Atkinson J, Westerink H, Smith J, Jensen B, Cox A, Cardonne V, Powell M (2006) High resolution unstructured grid storm surge modeling for Southern Louisiana. 5th Intl Workshop on Unstructured Grid Numerical Modeling of Coastal, Shelf & Ocean Flows, Nov 13–15, 2006
Yapa PD, Shen HT (1994) Modeling river oil-spills—a review. J Hydraul Res 32(5):765–782
Acknowledgements
The authors wish to acknowledge the financial support of the National Science Foundation’s IGERT Computational Fluid Dynamics program at LSU (Award #0504507), the Louisiana Department of Natural Resources and the GNOME Wizards at the National Oceanic Atmospheric Administration and the United States Army Corps of Engineers, ERDC, Coastal Hydraulics Laboratory for the support provided for this study.
Author information
Authors and Affiliations
Corresponding author
Additional information
Responsible editor: Lee Young
Rights and permissions
About this article
Cite this article
Danchuk, S., Willson, C.S. Effects of shoreline sensitivity on oil spill trajectory modeling of the Lower Mississippi River. Environ Sci Pollut Res 17, 331–340 (2010). https://doi.org/10.1007/s11356-009-0159-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-009-0159-8
Keywords
- Environmental sensitivity index mapping
- Oil spill modeling
- Shoreline oil interactions
- Shoreline sensitivity
- Shoreline retention