An approach to correct the effects of phytoplankton vertical nonuniform distribution on remote sensing reflectance of cyanobacterial bloom waters

Abstract

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 (Rrs(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 Rrs(λ) and Chl a inversion algorithms. Variations of ΔRrs(λ) (relative difference of Rrs(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 ΔRrs(λ) and Chl a(z) structure parameters. With knowledge of Chl a(z) profile parameters, Rrs(λ) of inhomogeneous waters can be corrected to the Rrs(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 Rrs and the Rrs correction performance.

Evaluation of Weighting Average Functions as a Simplification of the Radiative Transfer Simulation in Vertically Inhomogeneous Eutrophic Waters

“…Three field surveys were performed in Lake Chaohu in 2013 (28 May,(19)(20)(21)(22)(23)(24) July, and 10-12 October) [7]. Water samples were obtained from 9 depths (surface, 0.1, 0.2, 0.4, 0.7, 1.0, 1.5, 2.0, and 3.0 m) using an ad hoc vertical collection device.…”

“…In fact, the inhomogeneous distribution of phytoplankton considerably affects the spectrum shape and magnitude of R rs (λ) [18][19][20]. The differences in R rs (λ) between the vertical nonuniform and uniform water can be as high as >70% when the near-surface Chla decreases dramatically with depth [21]. Vertical variations of Chla(z) and IOPs(z) would introduce large errors in estimation of optical parameters using water color inversion algorithms built based on the assumption of vertical homogeneity [19,21,22].…”

“…Effects of Chla(z) vertical distribution on R rs (λ) and Chla estimation have been studied based on the relationship between R rs (λ) and structure parameters of Chla(z) profiles in Lake Chaohu, China [21]. With the knowledge of Chla(z) profile parameters, R rs (λ) of nonuniform waters can be corrected to the R rs (λ) of uniform waters with same average Chla across the water column [21]. However, structure parameters of Chla(z) profiles were difficult to obtain from R rs (λ).…”

Optical Classification of the Remote Sensing Reflectance and Its Application in Deriving the Specific Phytoplankton Absorption in Optically Complex Lakes

“…The slope coefficient of NAP absorption (S d ) and CDOM absorption (S g ) was calculated by fitting an exponential equation over 400-700 nm with 440 nm as the reference band [43]. Further details on the field measurements of the bio-optical parameters and processing methods can be found in previous studies [31,32,44].…”

Remote Sensing Estimation of Lake Total Phosphorus Concentration Based on MODIS: A Case Study of Lake Hongze

“…The TP could affect the growth and reproduction of plankton in the water [13], in addition, TP is associated with optical active constituents (OACs) in the water, including the SPM, Chla and chromogenic dissolved organic matter (CDOM) [12,14,15]. These three substances are the main substances that determine the optical characteristics of the water bodies [16][17][18]. Many studies have found the relationship between the spectral reflectance and TP by statistical methods, but there is no unified conclusion [19][20][21].…”