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Dynamic modelling of the spatio-temporal distribution of phytoplankton in a small productive English lake

Dynamic modelling of the spatio-temporal distribution of phytoplankton in a small productive English lake
Dynamic modelling of the spatio-temporal distribution of phytoplankton in a small productive English lake
The relationships between the spatio-temporal distribution of phytoplankton concentration and the environmental conditions of Esthwaite Water (a small eutrophic lake in the English Lake District, U.K.) were examined using a 3-D computational fluid dynamics (CFD) model. The water velocity field was obtained through solving the 3-D Navier Stokes equation for turbulent flow on a finite-volume, unstructured non-orthogonal grid. The spatio-temporal distributions of two types of phytoplankton were modelled: the cyanobacterium Microcystis, and the dinoflagellate Ceratium. Cyanobacterial buoyancy were estimated according to the Kromkamp and Walsby model, and dinoflagellate motility was estimated according to a model that we devised using empirical data from Esthwaite Water and other similar lakes. Circulation patterns of water and phytoplankton, as simulated by the CFD model, were similar to those obtained through field observations.
Downwind surface drift currents were initiated by wind stress, with sub-surface return gradient currents initiated near the thermocline. Near-surface accumulations of cyanobacteria were pushed downwind by the surface currents and accumulated at downwelling areas, and near-thermocline accumulations of dinoflagellates were pushed upwind by the sub-surface return currents, and accumulated at upwelling areas. In all cases, the Coriolis force greatly influenced patterns, causing a clockwise deflection of water flow and phytoplankton accumulation. Through the use of the CFD model, it was possible to conclude that the horizontal and vertical phytoplankton distributions resulted from the interaction between the vertical motility of the phytoplankton (dependent on the light environment) and the velocity vectors at the depths at which the phytoplankton accumulated (dependent upon wind stress and basin morphometry).
computational fluid dynamics, phytoplankton spatio-temporal distributions, velocity field, irradiance
Hedger, R.
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Olsen, N.
a11f4782-d2e8-4fea-a3f7-51cc63a095e5
George, D.G.
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Atkinson, P.M.
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Malthus, T.J.
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Hedger, R.
68efed4b-56cf-42a5-8033-02e854a4c9d1
Olsen, N.
a11f4782-d2e8-4fea-a3f7-51cc63a095e5
George, D.G.
a66d6633-1bab-4ddb-9ad5-2e954ff0beb5
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425
Malthus, T.J.
42dec45a-9314-4147-9cf6-029322bc1563

Hedger, R., Olsen, N., George, D.G., Atkinson, P.M. and Malthus, T.J. (1999) Dynamic modelling of the spatio-temporal distribution of phytoplankton in a small productive English lake. GeoComputation99 Fourth International Conference on GeoComputation, Fredericksburg, USA. 24 - 27 Jul 1999.

Record type: Conference or Workshop Item (Paper)

Abstract

The relationships between the spatio-temporal distribution of phytoplankton concentration and the environmental conditions of Esthwaite Water (a small eutrophic lake in the English Lake District, U.K.) were examined using a 3-D computational fluid dynamics (CFD) model. The water velocity field was obtained through solving the 3-D Navier Stokes equation for turbulent flow on a finite-volume, unstructured non-orthogonal grid. The spatio-temporal distributions of two types of phytoplankton were modelled: the cyanobacterium Microcystis, and the dinoflagellate Ceratium. Cyanobacterial buoyancy were estimated according to the Kromkamp and Walsby model, and dinoflagellate motility was estimated according to a model that we devised using empirical data from Esthwaite Water and other similar lakes. Circulation patterns of water and phytoplankton, as simulated by the CFD model, were similar to those obtained through field observations.
Downwind surface drift currents were initiated by wind stress, with sub-surface return gradient currents initiated near the thermocline. Near-surface accumulations of cyanobacteria were pushed downwind by the surface currents and accumulated at downwelling areas, and near-thermocline accumulations of dinoflagellates were pushed upwind by the sub-surface return currents, and accumulated at upwelling areas. In all cases, the Coriolis force greatly influenced patterns, causing a clockwise deflection of water flow and phytoplankton accumulation. Through the use of the CFD model, it was possible to conclude that the horizontal and vertical phytoplankton distributions resulted from the interaction between the vertical motility of the phytoplankton (dependent on the light environment) and the velocity vectors at the depths at which the phytoplankton accumulated (dependent upon wind stress and basin morphometry).

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More information

Published date: 1999
Venue - Dates: GeoComputation99 Fourth International Conference on GeoComputation, Fredericksburg, USA, 1999-07-24 - 1999-07-27
Keywords: computational fluid dynamics, phytoplankton spatio-temporal distributions, velocity field, irradiance

Identifiers

Local EPrints ID: 17661
URI: http://eprints.soton.ac.uk/id/eprint/17661
PURE UUID: 4e82fe2e-9673-4900-8a3d-fe8455e2182d

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Date deposited: 21 Oct 2005
Last modified: 11 Dec 2021 14:16

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Contributors

Author: R. Hedger
Author: N. Olsen
Author: D.G. George
Author: P.M. Atkinson
Author: T.J. Malthus

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