Bio-Optical Inversion in Highly Turbid and Cyanobacteria-Dominated Waters

Phytoplankton pigment absorption data from algal-bloom-dominated waters are highly desirable to better understand the primary productivity and carbon uptake by algal biomass in a regional scale. However, retrieving phytoplankton pigment absorption coefficients, in turbid and hypereutrophic waters, from above-surface remote sensing reflectance $(R_{rs})$ is often challenging because of the optical complexity of the water body. In this paper, a quasi-analytical algorithm has been parameterized using in situ data to retrieve inherent optical properties from $R_{rs}(\lambda )$ in highly turbid productive aquaculture ponds, where the phytoplankton absorption coefficient (3.44–37.67 $\hbox {m}^{-1}$ ) contributes $>$ 54 $%$ of the total absorption at 443 nm (4.99–47.21 $\hbox {m}^{-1}$ ). The model was validated using an independent data set by comparing the model-derived optical parameters with in situ measured values. The absolute percentage error (assuming no error in the in situ measurements) of the estimated total absorption coefficient $a_{t}( \lambda )$ varied from 15.22 $%$ to 24.13 $%$ within 413–665 nm, and the overall average error was 19.87 $%$ . Maximum and minimum errors occurred at 443 and 665 nm, respectively. Similarly, the percentage error for the phytoplankton absorption coeffi- ient $a_{\phi}(\lambda )$ varied from 15.9 $%$ to 41.27 $%$ within the 413–665-nm range, and the average error was 27.24 $%$ . The spectral shape of modeled $a_{\phi}(\lambda )$ matched very well $(R^{2} = 0.97)$ with the measured $a_{\phi}(\lambda )$ . A supplementary method was also developed to retrieve first-order estimates of colored detrital matter absorption coefficients $a_{\rm \rm CDM}( \lambda )$ from subsurface remote sensing reflectance $r_{rs}( \lambda )$ using an empirical approach. Results reveal that the retrieval accuracy of $a_{\phi}(\lambda )$ improved after incorporating the first-order estimates of $a_{\rm CDM}(\lambda )$ in the algorithm.