Moving source identification in an uncertain marine flow: Mediterranean Sea application
KAUST DepartmentKing Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia
Applied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Online Publication Date2020-12-09
Print Publication Date2021-01
Embargo End Date2022-12-01
Permanent link to this recordhttp://hdl.handle.net/10754/666648
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AbstractIdentifying marine pollutant sources is essential to assess, contain and minimize their risk. We propose a Lagrangian Particle Tracking algorithm (LPT) to study the transport of passive tracers advected by an uncertain flow field described by an ensemble of realizations of the ocean currents, and to identify the source parameters of the release in backward mode. Starting from a probability map describing the distribution of a pollutant, reverse tracking is used to generate probabilistic inverse maps by integrating it with the ensemble of flow fields backward in time. An objective function based on the probability-weighted distance between the resulting inverse maps and the source trajectory is then minimized to identify the likely source of pollution. We conduct numerical experiments to demonstrate the efficiency of the proposed algorithm in the Mediterranean Sea. Passive tracers are released along the path of a ship and propagated with an ensemble of realistic flow fields to generate a probability map, which is then used for the inverse problem of source identification. Our results suggest that the proposed algorithm captures the release time and source of pollution, successfully pinpointing to the release parameters up to two weeks back in time in certain case studies.
CitationHammoud, M. A. E. R., Lakkis, I., Knio, O., & Hoteit, I. (2020). Moving source identification in an uncertain marine flow: Mediterranean Sea application. Ocean Engineering, 108435. doi:10.1016/j.oceaneng.2020.108435
SponsorsResearch reported in this publication was supported by the Office of Sponsored Research (OSR) at King Abdullah University of Science and Technology (KAUST) CRG Award No. OSR-CRG2018-3711 and Virtual Red Sea Initiative (Grant #REP/1/3268-01-01) and by the University Research Board of the American University of Beirut (AUB). We acknowledge the use of E.U. Copernicus Marine Service Information available at https://doi.org/10.25423/MEDSEA_REANALYSIS_PHYS_006_004.