Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary

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, sin...

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Autores principales:	Neda Mardani, Mohammadreza Khanarmuei, Kabir Suara, Richard Brown, Adrian McCallum, Roy C. Sidle
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	estuary hydrodynamic model Lagrangian assimilation Eulerian assimilation residual currents OpenDA Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/1e4cd5c065684d23941424d654c940f6
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id	oai:doaj.org-article:1e4cd5c065684d23941424d654c940f6
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spelling	oai:doaj.org-article:1e4cd5c065684d23941424d654c940f62021-11-25T16:42:50ZLagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary10.3390/app1122110062076-3417https://doaj.org/article/1e4cd5c065684d23941424d654c940f62021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/11006https://doaj.org/toc/2076-3417Numerical 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.Neda MardaniMohammadreza KhanarmueiKabir SuaraRichard BrownAdrian McCallumRoy C. SidleMDPI AGarticleestuaryhydrodynamic modelLagrangian assimilationEulerian assimilationresidual currentsOpenDATechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 11006, p 11006 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	estuary hydrodynamic model Lagrangian assimilation Eulerian assimilation residual currents OpenDA Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	estuary hydrodynamic model Lagrangian assimilation Eulerian assimilation residual currents OpenDA Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Neda Mardani Mohammadreza Khanarmuei Kabir Suara Richard Brown Adrian McCallum Roy C. Sidle Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary
description	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.
format	article
author	Neda Mardani Mohammadreza Khanarmuei Kabir Suara Richard Brown Adrian McCallum Roy C. Sidle
author_facet	Neda Mardani Mohammadreza Khanarmuei Kabir Suara Richard Brown Adrian McCallum Roy C. Sidle
author_sort	Neda Mardani
title	Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary
title_short	Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary
title_full	Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary
title_fullStr	Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary
title_full_unstemmed	Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary
title_sort	lagrangian data assimilation for improving model estimates of velocity fields and residual currents in a tidal estuary
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/1e4cd5c065684d23941424d654c940f6
work_keys_str_mv	AT nedamardani lagrangiandataassimilationforimprovingmodelestimatesofvelocityfieldsandresidualcurrentsinatidalestuary AT mohammadrezakhanarmuei lagrangiandataassimilationforimprovingmodelestimatesofvelocityfieldsandresidualcurrentsinatidalestuary AT kabirsuara lagrangiandataassimilationforimprovingmodelestimatesofvelocityfieldsandresidualcurrentsinatidalestuary AT richardbrown lagrangiandataassimilationforimprovingmodelestimatesofvelocityfieldsandresidualcurrentsinatidalestuary AT adrianmccallum lagrangiandataassimilationforimprovingmodelestimatesofvelocityfieldsandresidualcurrentsinatidalestuary AT roycsidle lagrangiandataassimilationforimprovingmodelestimatesofvelocityfieldsandresidualcurrentsinatidalestuary
_version_	1718413004120260608

Lagrangian Data Assimilation for Improving Model Estimates of Velocity Fields and Residual Currents in a Tidal Estuary

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