Hydrodynamic modelling and characterisation of a shallow fluvial lake: a study on the Superior Lake of Mantua

Submitted: 30 October 2015
Accepted: 24 March 2016
Published: 19 April 2016
Abstract Views: 1922
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This paper presents a numerical modelling framework developed to simulate circulations and to generally characterise the hydrodynamics of the Superior Lake of Mantua, a shallow fluvial lake in Northern Italy. Such eutrophied basin is characterised by low winds, reduced discharges during the summer and by the presence of large lotus flower (Nelumbo nucifera) meadows, all contributing to water stagnation. A hydrodynamic numerical model was built to understand how physical drivers shape basic circulation dynamics, selecting appropriate methodologies for the lake. These include a 3D code to reproduce the interaction between wind and through-flowing current, a fetch-dependent wind stress model, a porous media approach for canopy flow resistance and the consideration of wave-current interaction. The model allowed to estimate the circulation modes and water residence time distributions under identified typical ordinary, storm and drought conditions, the hydrodynamic influence of the newly-opened secondary outlet of the lake, the surface wave parameters, their influence on circulations and the bottom stress they originate, and the adaptation time scales of circulations to storm events. Some probable effects of the obtained hydrodynamic characteristics of the Superior Lake of Mantua on its biochemical processes are also introduced.



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Andrea Fenocchi, University of Pavia
Research Assistant in Hydraulics at the Department of Civil Engineering and Architecture of the University of Pavia
Stefano Sibilla, University of Pavia
Associate Professor in Hydraulics at the Department of Civil Engineering and Architecture of the University of Pavia

How to Cite

Fenocchi, Andrea, and Stefano Sibilla. 2016. “Hydrodynamic Modelling and Characterisation of a Shallow Fluvial Lake: A Study on the Superior Lake of Mantua”. Journal of Limnology 75 (3). https://doi.org/10.4081/jlimnol.2016.1378.

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