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Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary7.44 MB
Published VersionCC BY V4.0, Open Access
Journal article
Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary
Applied Sciences, Vol.11(22), pp.1-26
2021
Abstract
Numerical models are associated with uncertainties that can be reduced through data assimilation (DA). Lower costs have driven a recent tendency to use Lagrangian instruments such as drifters and floats to obtain information about water bodies. However, difficulties emerge in their assimilation, since Lagrangian data are set out in a moving frame of reference and are not compatible with the fixed grid locations used in models to predict flow variables. We applied a pseudo-Lagrangian approach using OpenDA, an open-source DA tool to assimilate Lagrangian drifter data into an estuarine hydrodynamic model. Despite inherent challenges with using drifter datasets, the work showed that low-cost, low-resolution drifters can provide a relatively higher improvement over the Eulerian dataset due to the larger area coverage of the drifter. We showed that the assimilation of Lagrangian data obtained from GPS-tracked drifters in a tidal channel for a few hours can significantly improve modelled velocity fields (up to 30% herein). A 40% improvement in residual current direction was obtained when assimilating both Lagrangian and Eulerian data. We conclude that the best results are achieved when both Lagrangian and Eulerian datasets are assimilated into the hydrodynamic model.
Details
- Title
- Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary
- Authors
- Neda Mardani (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringMohammadreza Khanarmuei (Author) - Queensland University of TechnologyKabir Suara (Author) - Queensland University of TechnologyRichard Brown (Author) - Queensland University of TechnologyAdrian McCallum (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringRoy C Sidle (Author) - University of the Sunshine Coast
- Publication details
- Applied Sciences, Vol.11(22), pp.1-26
- Publisher
- MDPI AG
- Date published
- 2021
- DOI
- 10.3390/app112211006
- ISSN
- 2076-3417
- Copyright note
- Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Organisation Unit
- Indigenous and Transcultural Research Centre; University of the Sunshine Coast, Queensland; Cancer Research Cluster; School of Science, Technology and Engineering; Sustainability Research Cluster
- Language
- English
- Record Identifier
- 99594505202621
- Output Type
- Journal article
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- Web Of Science research areas
- Chemistry, Multidisciplinary
- Engineering, Multidisciplinary
- Materials Science, Multidisciplinary
- Physics, Applied
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