A Spatial Decision Support System for Oil Spill Response and Recovery

Abstract

abstract: 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.Dissertation/ThesisMasters Thesis Computer Science 201