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Using 3D modeling and remote sensing capabilities for a better understanding of spatio-temporal heterogeneities of phytoplankton abundance in large lakes

Abstract : Lake biological parameters show important spatio-temporal heterogeneities. This is why explaining the spatial patchiness of phytoplankton abundance has been a recurrent ecological issue and is an essential prerequisite for objectively assessing, protecting and restoring freshwater ecosystems. The drivers of these heterogeneities can be identified by modelling their dynamics. This approach is useful for theoretical and applied limnology. In this study, a 3D hydrodynamic model of LakeGeneva (France/Switzerland) was created. It is based on the Delft3D suite software and includes the main tributary (Rhône River) and two-dimensional high-resolution meteorological forcing. It provides 3D maps of water temperature and current velocities with a 1 h time step on a 1 km horizontal grid size and with a vertical resolution of 1 m near the surface to 7 m at the bottom of the lake. The dynamics and the drivers of phytoplankton heterogeneities were assessed by combining the outputs of the model and chlorophyll-a concentration (Chl-a) data from MERIS satellite images between 2008 and 2012. Results highlight physical mechanisms responsible for the occurrence of seasonal hot-spots in phytoplankton abundance in the lake. At the beginning of spring, Chl-a heterogeneities are usually caused by an earlier onset of phytoplankton growth in the shallowest and more sheltered areas; spatial differences in the timing of phytoplankton growth can be explained by spatial variability in thermal stratification dynamics. In summer, transient and locally higher phytoplankton abundances are observed in relation to the impact of basin-scale upwelling.
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https://hal.inrae.fr/hal-02608363
Contributor : Migration Irstea Publications <>
Submitted on : Saturday, May 16, 2020 - 4:01:30 PM
Last modification on : Friday, July 10, 2020 - 10:14:07 AM

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  • HAL Id : hal-02608363, version 1
  • IRSTEA : PUB00059632

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Frédéric Soulignac, P.A. Danis, D. Bouffard, V. Chanudet, E. Dambrine, et al.. Using 3D modeling and remote sensing capabilities for a better understanding of spatio-temporal heterogeneities of phytoplankton abundance in large lakes. Journal of Great Lakes Research, Elsevier, 2018, 44, pp.756-764. ⟨hal-02608363⟩

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