A statistical representation of oil spill fate in the Salish Sea (Part 2)

Abstract

We use a novel approach that combines Automatic Identification System (AIS) ship traffic data, state regulated oil transfer data, and a suite of numerical models to statistically represent the risk of spilled Alaska North Slope Crude, Bunker-C, and Marine Diesel under a variety of environmental conditions in an estuarine environment off the northeastern Pacific Ocean. We show the statistics of fate and transport outcomes based on 10,000 MOHID oil spill model simulations with currents, winds, and waves between January 1, 2015 and December 31, 2018. Each of the 10,000 oil spill scenarios was run individually and includes weathering from biodegradation, dissolution, dispersion, emulsification, evaporation, and spreading. Our pioneering approach captures statistical variability in seasonality, vessel traffic, spill locations, and oil types. We show that heterogeneity of 3D circulation in an estuarine environment, combined with marine traffic "footprints", creates regionally-variable signatures of the timing, likelihood and type of potential oiling.

Keywords: Indigenous reconciliation; Monte Carlo; Oil spill modeling; Salish Sea; Shipping risks.