Exploiting high frequency monitoring and satellite imagery for assessing chlorophyll-a dynamics in a shallow eutrophic lake

Freshwater ecosystems are challenged by cultural eutrophication across the globe, and it is a priority for water managers to implement water quality monitoring at different spatio-temporal scales to control and mitigate the eutrophication process. Phytoplankton abundance is a key indicator of the trophic and water quality status of lakes. Phytoplankton dynamics are characterized by high spatio-temporal variation, driven by physical, chemical and biological factors, that challenge the capacity of routine monitoring with conventional sampling techniques (i.e., boat based sampling) to characterise these complex relationships. In this study, high frequency in situ measurements and multispectral satellite data were used in a synergistic way to explore temporal (diurnal and seasonal) dynamics and spatial distribution of Chlorophyll-a (Chl-a) concentration, a proxy of phytoplankton abundance, together with physico-chemical water parameters in a shallow fluvial-lake system (Mantua Lakes). A good agreement was found between Chl-a retrieved by remote sensing data and Chl-a fluorescence data recorded by multi-parameters probes (R2 = 0.94). The Chl-a maps allowed a seasonal classification of the Mantua Lakes system as eutrophic or hypertrophic. Along the Mantua lakes system an increasing gradient in Chl-a concentration was recorded following the transition from a fluvial to lacustrine system. There was significant seasonal heterogeneity among the sub-basins, probably due to different hydrodynamics, influenced also by macrophyte stands. High-frequency data revealed the importance of rainfall events in the timing and growth dynamics of phytoplankton, particularly for spring and late summer blooms. Combining temporal and spatial data at high resolution improves the understanding of complex fluvial-lake systems. This technique can allow managers to target blooms in near-real time as they move through a system and guide them to localized hot spots enabling timely management action in ecosystems of high conservation and recreational value.

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

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 (<em>Nelumbo</em> <em>nucifera</em>) 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.