Modelling the inherent optical properties and estimating the constituents' concentrations in turbid and eutrophic waters

Retrieval of the inherent optical properties and estimation of the constituents' concentrations from satellite ocean colour data in turbid and eutrophic waters are important as these products provide innovative opportunities for the study of biological and biogeochemical properties in such optically complex waters. This paper intends to develop models to retrieve absorption coefficients of phytoplankton, suspended sediments and coloured dissolved organic matter and describe vertical profiles of chlorophyll and suspended sediments from satellite ocean colour data. These models make use of the relationships between remote sensing reflectance ratios Rrs (555)/Rrs (443) and Rrs (620)/Rrs (490) versus aph (443) and aph (555), and acdom (443), and ad (443) to derive the model parameters. Validation with the in-situ data obtained from coastal waters around India and other regional waters (e.g., NASA bio-Optical Marine Algorithm Data-Set, NOMAD) shows that the new models are more accurate in terms of producing the spectral absorption coefficients (aph, ad, acdom across the entire visible wavelengths 400-700nm) in a wide variety of waters. Further comparison with existing models shows advantage of the new models that have important implications for remote sensing of turbid coastal and eutrophic waters. The retrieved absorption coefficients of phytoplankton and suspended sediments (non-algal matter) are also found to relate better to chlorophyll and total suspended sediments. Taking advantages of this, we derive models to determine and describe the vertical profiles of chlorophyll and suspended sediment concentrations along the depth. The model parameters are derived empirically. These new parameterizations show potential in estimating the vertical profiles of chlorophyll and suspended sediments with good accuracy. These results suggest robustness and suitability of the new models for studying the ecologically important components of optically complex turbid and eutrophic waters using remote sensing data. © 2014 Elsevier Ltd.