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BAKTRAK: backtracking drifting objects using an iterative algorithm with a forward trajectory model


The task of determining the origin of a drifting object after it has been located is highly complex due to the uncertainties in drift properties and environmental forcing (wind, waves, and surface currents). Usually, the origin is inferred by running a trajectory model (stochastic or deterministic) in reverse. However, this approach has some severe drawbacks, most notably the fact that many drifting objects go through nonlinear state changes underway (e.g., evaporating oil or a capsizing lifeboat). This makes it difficult to naively construct a reverse-time trajectory model which realistically predicts the earliest possible time the object may have started drifting. We propose instead a different approach where the original (forward) trajectory model is kept unaltered while an iterative seeding and selection process allows us to retain only those particles that end up within a certain time–space radius of the observation. An iterative refinement process named BAKTRAK is employed where those trajectories that do not make it to the goal are rejected, and new trajectories are spawned from successful trajectories. This allows the model to be run in the forward direction to determine the point of origin of a drifting object. The method is demonstrated using the leeway stochastic trajectory model for drifting objects due to its relative simplicity and the practical importance of being able to identify the origin of drifting objects. However, the methodology is general and even more applicable to oil drift trajectories, drifting ships, and hazardous material that exhibit nonlinear state changes such as evaporation, chemical weathering, capsizing, or swamping. The backtracking method is tested against the drift trajectory of a life raft and is shown to predict closely the initial release position of the raft and its subsequent trajectory.

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This work was made possible by funding from the Norwegian Defence Research Establishment (FFI) through the BAKTRAK project. The field work was organized and partly funded by the project “Uncontrolled drift of ships and larger objects,” funded by the Research Council of Norway (NFR) under the MAROFF programme (grant no. 200862). The analysis has also benefited from the MAROFF project FARGE (grant no. 200843). The authors wish to thank the Joint Rescue Co-ordination Centres (JRCC) and the Norwegian Navy for their continued support of the development of operational trajectory models for search and rescue. This work builds on results from the SAR-DRIFT project under the French-Norwegian Foundation (Eureka grant E!3652) and the FOB project funded through the NFR MAROFF programme (grant no. 180175). This project has also benefited from the Norwegian National Supercomputing Facility (NOTUR). Finally, we wish to thank the two anonymous reviewers for their thorough scrutiny of the manuscript which made us include important new material.

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Correspondence to Øyvind Breivik.

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This article is part of the Topical Collection on Maritime Rapid Environmental Assessment

Responsible Editor: Michel Rixen

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Breivik, Ø., Bekkvik, T.C., Wettre, C. et al. BAKTRAK: backtracking drifting objects using an iterative algorithm with a forward trajectory model. Ocean Dynamics 62, 239–252 (2012).

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  • Trajectory modeling
  • Search and rescue
  • Operational oceanography
  • Backtracking drifting objects
  • Inverse methods