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Performance Assessment of a 3D Hydrodynamic Model Using High Temporal Resolution Measurements in a Shallow Urban Lake

Abstract : Urban lakes provide many ecosystem services, e.g., flood control, nature protection, coolness island, recreation. Hydrodynamic models will increasingly be used to enhance these benefits. We present the first validation of a three-dimensional (3D) hydrodynamic model on a small shallow lake with high resolution and high frequency measurements. Lake Créteil, France (area 0.4 km2, mean depth 4.5 m, and catchment area 1 km2) is a former gravel pit and now part of a regional park. The model Delft3D-FLOW was calibrated on a one-month period, with continuous measurements of temperature at five depths at the center of the lake and at three depths at two other stations, and with current speed profiles at the centre of the lake. The model was then verified on 18 1-month periods with similar temperature measurements. The model reproduced very well the temperature dynamics, including the alternation between mixing and stratification periods and internal wave patterns. The mean absolute errors over the five depths at the central point remained below 0.55∘C in spring and summer, the most favorable seasons for phytoplankton growth. Horizontal temperature differences, which rose up to 3∘C at the beginning of stratification periods, were also well reproduced, as well as current speeds. These results are very promising for assessing nutrient and pollutant diffusion, settling and resuspension, as well as for understanding how phytoplankton blooms start in small shallow lakes.
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Contributeur : Brigitte Vinçon-Leite <>
Soumis le : lundi 7 mai 2018 - 16:34:12
Dernière modification le : mercredi 8 janvier 2020 - 15:28:03
Document(s) archivé(s) le : lundi 24 septembre 2018 - 21:33:15


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Frédéric Soulignac, Brigitte Vinçon-Leite, Bruno J. Lemaire, José Scarati Martins, Céline Bonhomme, et al.. Performance Assessment of a 3D Hydrodynamic Model Using High Temporal Resolution Measurements in a Shallow Urban Lake. Environmental Modeling & Assessment, Springer, 2017, 22 (4), pp.309-322. ⟨10.1007/s10666-017-9548-4⟩. ⟨hal-01770079⟩



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