Journal
REMOTE SENSING OF ENVIRONMENT
Volume 157, Issue -, Pages 185-198Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2014.06.013
Keywords
Remote sensing; Bio-optical model; Hydrodynamic modeling; Horizontal surface phytoplankton distribution; Mixing regimes
Funding
- INCT for Climate Change [CNPq 5737797/2008, FAPESP 08/57719-9]
- Sao Paulo Research Foundation (FAPESP) [2007/08103-2]
- Brazilian Council of Technological and Scientific Development (CNPq) [161233/2013-9]
- Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES)
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The goal of this study was to determine the extent to which mixing and stratification processes influence the horizontal surface phytoplankton distribution in a tropical hydroelectric reservoir in Brazil. We used a synergistic approach that combines remote sensing bio-optical empirical and three-dimensional hydrodynamic modeling to represent phytoplankton dynamics. Seasonal differences were evaluated by simulating the bio-optical and the three-dimensional hydrodynamic models for two periods: the austral summer and winter of 2009. The three-dimensional hydrodynamic model simulations showed that the water column was completely mixed during winter; the water column remained stratified during summer. We also noticed a permanent thermocline during the summer between 15 and 25 m in the reservoir. In both seasons, the surface current was wind driven and preferentially directed eastward. The bio-optical model showed that the horizontal surface phytoplankton distribution, as indicated by chlorophyll-a concentration, was heterogeneous during winter and homogenous during summer. Moreover, higher concentrations were observed by the empirical bio-optical model during winter (the highest mean areal concentration was 24 mu g L-1) than in summer (2.1 mu g L-1). This difference was explained by short timescale events, such as cold front passages, which contributed to the proliferation of phytoplankton in winter by enhancing vertical mixing in the water column. Lake number analysis showed that upwelling events were the most common mechanisms driving the mixing process during winter (L-N < 1 82% of the time). Combining remote sensing and three-dimensional hydrodynamic modeling makes it possible to more fully analyze the dynamics of the horizontal surface phytoplankton distribution under different meteorological conditions. The two modeling techniques can be used in a complementary manner and serve as an essential tool for the environmental monitoring of aquatic systems. (C) 2014 Elsevier Inc. All rights reserved.
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