Assessing Potential Algal Blooms in a Shallow Fluvial Lake by Combining Hydrodynamic Modelling and Remote-Sensed Images

Abstract: Shallow fluvial lakes are dynamic ecosystems shaped by physical and biological factors and characterized by the coexistence of phytoplankton and macrophytes. Due to multiple interplaying factors, understanding the distribution of phytoplankton in fluvial lakes is a complex but fundamental issue, in the context of increasing eutrophication, climate change, and multiple water uses. We analyze the distribution of phytoplankton by combining remotely sensed maps of chlorophyll- a with a hydrodynamic model in a dammed fluvial lake (Mantua Superior Lake, Northern Italy). The numerical simulation of different conditions shows that the main hydrodynamic effects which influence algal distribution are related to the combined effect of advection due to wind forces and local currents, as well as to the presence of large gyres which induce recirculation and stagnation regions, favoring phytoplankton accumulation. Therefore, the general characters of the phytoplankton horizontal patchiness can be inferred from the results of the hydrodynamic model. Conversely, hyperspectral remote-sensing products can be used to validate this model, as they provide chlorophyll-

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