Assimilative 2-D Lagrangian Transport Model for the Estimation of Oil Leakage Parameters From SAR Images: Application to the Montara Oil Spill

Abstract

Indonesia is particularly vulnerable to oil spill since Indonesian waters, which account for 80% of its territory, involve a very active maritime traffic and a large number of onshore and offshore oil platforms. Within the framework of Infrastructure Development Space Oceanography project, we address the operational synthetic aperture radar (SAR) based monitoring of oil spill in Indonesian waters from space. This work focuses on the assimilation of SAR observations into a 2-D Lagrangian trajectory model. The simulated surface oil trajectories are compared to the satellite observations in subsequent forecast cycles for veracity testing by estimating best leakage parameters of detected oil spills. As a case study, we consider a large oil spill event that took place in Indonesian waters in Fall 2009, referred to as the Montara oil spill. A novel methodology has been developed, which combines SAR-based oil spill detection using a Lagrangian analysis and numerical tools. Our model relies on four key parameters: wind-related and current-related drift parameters, and the origin and the duration of the oil leakage. Given an SAR-derived oil spill detection, a numerical inversion is used to optimize these model parameters, so that the simulated drift matches the SAR-derived observation. The demonstration of the relevance of the proposed scheme for the Montara oil spill and further discussion on operational interest for satellite-based oil spill monitoring can be useful in rapid response system in Indonesia.