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An approach to correct the effects of phytoplankton vertical nonuniform distribution on remote sensing reflectance of cyanobacterial bloom waters
Author(s) -
Xue Kun,
Zhang Yuchao,
Ma Ronghua,
Duan Hongtao
Publication year - 2017
Publication title -
limnology and oceanography: methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.898
H-Index - 72
ISSN - 1541-5856
DOI - 10.1002/lom3.10158
Subject(s) - water column , phytoplankton , environmental science , chlorophyll a , eutrophication , homogeneous , radiative transfer , atmospheric sciences , physics , oceanography , chemistry , ecology , geology , biology , nutrient , optics , biochemistry , thermodynamics
Cyanobacterial blooms occur frequently in eutrophic lakes and their potentially harmful effects affected the security of drinking water and food sources, biodiversity, and economic activities, and attracted the attention of general public worldwide. Cyanobacteria could move vertically in the water column by regulating their buoyancy, which leads to the assumption of homogeneous water invalid. Ecolight, based on radiative transfer theory, was applied to examine the effects of vertical nonuniform of chlorophyll a concentrations (Chl a ( z )) on remote sensing reflectance spectrum ( R rs ( λ )) of optically complex inland waters. Simulations for nonuniform water consisting of three Chl a ( z ) profile classes, including Gaussian, exponential, and power, were compared with simulations for a reference homogeneous water whose Chl a was identical to average value of the nonuniform case. The near‐surface aggregation of phytoplankton are shown to have significant influence on R rs ( λ ) and Chl a inversion algorithms. Variations of Δ R rs ( λ ) (relative difference of R rs ( λ ) between inhomogeneous and homogeneous waters with same average Chl a concentration) mainly depended on the Chl a ( z ) structure parameters and wavelength. A correction scheme was developed based on the relationships between Δ R rs ( λ ) and Chl a ( z ) structure parameters. With knowledge of Chl a ( z ) profile parameters, R rs ( λ ) of inhomogeneous waters can be corrected to the R rs ( λ ) of uniform waters with same average Chl a across the water column. Examples of field data from Lake Chaohu illustrated the effects of phytoplankton variation on the near infrared‐to‐red ratio of R rs and the R rs correction performance.