Maps of oil spill probability are important tools in environmental risk assessment and decision making in coastal zone management. In a new paper appearing in the journal Ocean & Coastal Management, a research team led by Sahar Mokhtari outlines their development of a predictive model that relates reported oil spill events to four explanatory variables and provides estimates of the spatial distribution of oil spill risks. Using case studies of the northern Persian Gulf, they found that ship routes, coastlines, oil wells, and oil facilities can be used as proxies of oil spill risk and they implemented the oil spill risk prediction model in open source software.

Mokhtari is a PhD candidate at Tarbiyat Modares University in Iran who is currently a visiting research scholar in Louisiana State University. She worked as the senior expert on coastal environment for the project and the topic of her PhD thesis is designing of decision support system for the protection of coasts from oil spills.

According to the paper’s abstract, “In the northern part of the Persian Gulf, the largest probability of oil spills was predicted in areas where actual oil facilities in combination with high intensity ship traffic are in evidence.”

The authors state that their model “can predict the probability of oil spills as raster map in a standard R data format. It can be used in environmental risk assessment as well as an input for more detailed oil spill simulation models. The advantages of the model include its’ high spatial resolution, accounting for uncertainty in oil spill locations, and the possibility of sharing as an open-source R script with other users.”

The original paper is available here.