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Model output for marine debris accumulating at Seychelles and other remote islands in the western Indian Ocean (1993-2019)

Update Frequency: Not Planned
Latest Data Update: 2022-12-07
Status: Completed
Online Status: ONLINE
Publication State: Citable
Publication Date: 2022-12-13
DOI Publication Date: 2022-12-13
Download Stats: last 12 months
Dataset Size: 12.0K Files | 968GB


This dataset contains raw beaching data computed by marine debris simulations (run using OceanParcels) for a range of physical scenarios (surface currents from GLORYS12V1 (, Stokes drift from WAVERYS (, and surface winds from ERA5 (, as described in the accompanying manuscript. Through postprocessing, debris ‘connectivity’ matrices can be computed, providing predictions for the main terrestrial and marine source regions of plastic debris accumulating at remote islands in the western Indian Ocean. These simulations include beaching and sinking processes, and a set of example matrices is provided here ( However, these matrices can be recomputed for different sinking and beaching rates using the scripts archived here (, or see here ( for the live version with documentation. These predictions will be useful for environmental practitioners in the western Indian Ocean to assess source regions for marine debris accumulating at islands of interest, and when this debris is likely to beach. The data were produced as part of the Marine Dispersal and Retention in the Western Indian Ocean project funded by the Natural Environment Research Council (NERC) grant NE/S007474/1. See linked online references on this record for cited items given above.

Citable as:  Vogt-Vincent, N.; Johnson, H. (2022): Model output for marine debris accumulating at Seychelles and other remote islands in the western Indian Ocean (1993-2019). NERC British Oceanographic Data Centre, 13 December 2022. doi:10.5285/fc001b104fe6458e92ab6a0be314e68e.
Abbreviation: Not defined
Keywords: Indian Ocean, Plastic, Pollution, Marine debris, Seychelles, Fisheries, ALDFG, Lagrangian, Monsoon, Model


Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

This dataset consists of modelled large scale dispersal experiments across the southwestern Indian Ocean. The simulations were funded through PhD project NE/S007474/1, Marine dispersal and retention in the western Indian Ocean, held by Noam Vogt-Vincent who was supervised by Helen Johnson, both at University of Oxford. The outputs are archived on the British Oceanographic Data Centre (BODC)'s space at the Centre for Environmental Data Analysis (CEDA) and assigned a DOI. No quality control procedures were applied by BODC.

Data Quality:
The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). The data suppliers have not indicated if any quality control has been undertaken on these data.
File Format:
Data are CF-Compliant NetCDF formatted data files

Process overview

This dataset was generated by the computation detailed below.

Ocean Parcels


The OceanParcels project develops Parcels (Probably A Really Computationally Efficient Lagrangian Simulator), a set of Python classes and methods to create customisable particle tracking simulations using output from Ocean Circulation models. Parcels can be used to track passive and active particulates such as water, plankton, plastic and fish. The code from the OceanParcels project is licensed under an open source MIT license and can be downloaded from or installed via

Input Description


Output Description


Software Reference


  • var_id: cp0
  • var_id: e0
  • var_id: e1
  • var_id: e10
  • var_id: e11
  • var_id: e12
  • var_id: e13
  • var_id: e14
  • var_id: e15
  • var_id: e16
  • var_id: e17
  • var_id: e18
  • var_id: e19
  • var_id: e2
  • var_id: e20
  • var_id: e21
  • var_id: e22
  • var_id: e23
  • var_id: e24
  • var_id: e25
  • var_id: e26
  • var_id: e27
  • var_id: e28
  • var_id: e29
  • var_id: e3
  • var_id: e30
  • var_id: e31
  • var_id: e32
  • var_id: e33
  • var_id: e34
  • var_id: e4
  • var_id: e5
  • var_id: e6
  • var_id: e7
  • var_id: e8
  • var_id: e9
  • var_id: e_num
  • var_id: gfw_num
  • var_id: lat0
  • var_id: lon0
  • var_id: origin_iso
  • var_id: rp0
  • var_id: traj

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