A Spatial Decision Support System for Oil Spill Response and Recovery

Coastal areas are susceptible to man-made disasters, such as oil spills, which not

only have a dreadful impact on the lives of coastal communities and businesses but also

have lasting and hazardous consequences. The United States coastal areas, especially

the Gulf of Mexico, have witnessed devastating oil spills of varied sizes and durations

that resulted in major economic and ecological losses. These disasters affected the oil,

housing, forestry, tourism, and fishing industries with overall costs exceeding billions

of dollars (Baade et al. (2007); Smith et al. (2011)). Extensive research has been

done with respect to oil spill simulation techniques, spatial optimization models, and

innovative strategies to deal with spill response and planning efforts. However, most

of the research done in those areas is done independently of each other, leaving a

conceptual void between them.

In the following work, this thesis presents a Spatial Decision Support System

(SDSS), which efficiently integrates the independent facets of spill modeling techniques

and spatial optimization to enable officials to investigate and explore the various

options to clean up an offshore oil spill to make a more informed decision. This

thesis utilizes Blowout and Spill Occurrence Model (BLOSOM) developed by Sim

et al. (2015) to simulate hypothetical oil spill scenarios, followed by the Oil Spill

Cleanup and Operational Model (OSCOM) developed by Grubesic et al. (2017) to

spatially optimize the response efforts. The results of this combination are visualized

in the SDSS, featuring geographical maps, so the boat ramps from which the response

should be launched can be easily identified along with the amount of oil that hits the

shore thereby visualizing the intensity of the impact of the spill in the coastal areas

for various cleanup targets.