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Water 2015, 7(5), 1921-1942; doi:10.3390/w7051921

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

1
Institute for Electromagnetic Sensing of the Environment, National Research Council, Via Bassini 15, Milan 20133, Italy
2
Department of Life Sciences, University of Parma, Viale Usberti 11/a, Parma 43124, Italy
3
Department of Civil Engineering and Architecture, University of Pavia, Via Ferrata 3, Pavia 27100, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Say-Leong Ong
Received: 2 February 2015 / Revised: 11 April 2015 / Accepted: 24 April 2015 / Published: 28 April 2015
(This article belongs to the Special Issue Water Quality Control and Management)
View Full-Text   |   Download PDF [2490 KB, uploaded 9 June 2015]   |  

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-a distribution maps. The integration of ecological, hydraulic, and remote-sensing techniques may therefore help the monitoring and protection of inland water quality, with important improvements in management actions by policy makers. View Full-Text
Keywords: fluvial lake; chlorophyll-a distribution; water circulation; hydrodynamic model; remote sensing; hyperspectral data; water resource management fluvial lake; chlorophyll-a distribution; water circulation; hydrodynamic model; remote sensing; hyperspectral data; water resource management
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Pinardi, M.; Fenocchi, A.; Giardino, C.; Sibilla, S.; Bartoli, M.; Bresciani, M. Assessing Potential Algal Blooms in a Shallow Fluvial Lake by Combining Hydrodynamic Modelling and Remote-Sensed Images. Water 2015, 7, 1921-1942.

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