A Bayesian Network Risk Model for Oil Spill Response Effectiveness in the Canadian Arctic (OSRECA)
Abstract
A Bayesian Network Model is used to aid in understanding the effectiveness of oil spill responses for various scenarios in the Canadian Arctic. While the proposed model can be used as a basis for exploring response effectiveness, adequate attention to the strength of evidence on which the model is built is required. Hence, a strength of evidence, sensitivity analysis, and criticality matrix supplements the risk model, to provide information on the sensitivity of the effectiveness of the sub-models and the evidence on which the model is based. This thesis aimed to generate a Bayesian Network model to provide insights in oil spill response processes, focused on the effectiveness of different response operations in selected conditions. Ten unique sub-models were created for the three main response types: Mechanical Recovery, Chemical Dispersant, and In-Situ Burning