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

Frédéric Soulignac; Pierre-Alain Danis; Damien Bouffard; Vincent Chanudet; Etienne Dambrine; Yann Guénand; Tristan Harmel; Bastiaan W. Ibelings; Dominique Trevisan; Rob Uittenbogaard; Orlane Anneville

doi:10.1016/j.jglr.2018.05.008

Article dans une revue

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

Frédéric Soulignac ¹ Pierre-Alain Danis ² Damien Bouffard ³ Vincent Chanudet ⁴ Etienne Dambrine ¹ Yann Guénand ¹ Tristan Harmel ^{5, 6} Bastiaan W. Ibelings ⁷ Dominique Trevisan ¹ Rob Uittenbogaard ⁸ Orlane Anneville ¹

1 CARRTEL - Centre Alpin de Recherche sur les Réseaux Trophiques et Ecosystèmes Limniques

2 Pôle AFB-Irstea hydroécologie plans d'eau

3 EAWAG - Swiss Federal Institute of Aquatic Science and Technology

4 CIH, centre d'ingénierie hydraulique

5 Sorbonne Universités (COMUE)

6 IRSTEA - Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture

7 Department F.-A. Forel for Environmental and Aquatic Sciences

8 Deltares

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 modeling their dynamics. This approach is useful for theoretical and applied limnology. In this study, a 3D hydrodynamic model of Lake Geneva (France/Switzerland) was created. It is based on the Delft3D suite software and includes the main tributary (Rhone 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.

Keywords : 3D modeling remote sensing chlorophyll-alpha spatio-temporal heterogeneity lake Geneva Delft3D

Type de document :

Article dans une revue

Domaine :

Sciences du Vivant [q-bio]

Liste complète des métadonnées

https://hal.inrae.fr/hal-02628548
Déposant : Migration Prodinra <>
Soumis le : mardi 26 mai 2020 - 23:22:36
Dernière modification le : vendredi 6 novembre 2020 - 03:34:52

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

Lien texte intégral

Identifiants

Collections

Citation

Exporter

Métriques

22

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

Lien texte intégral

Identifiants

Collections

Citation

Exporter

Partager

Métriques

22