A model is developed for deriving the backscattering properties of phytoplankton [bbph(λ)] and nonalgal particles [bbNAP(λ)] from the total particulate backscattering coefficient [bbp(λ)] in turbid and productive coastal and inland water environments. In situ spectral particulate backscattering data acquired from several field campaigns on the turbid and productive coastal regions of southern India are used to develop a partitioning method and establish robust relationships between the partitioned bbph(λ) and bbNAP(λ) versus chlorophyll and turbidity. The performance of this method is assessed using independent data sets from marine and inland productive waters. The bbph(λ) and bbNAP(λ) products derived from this method are found in good agreement with in situ data, with the overall percentile error of a few percent which is well within the benchmark for a validated uncertainty of ±35% endorsed for the chlorophyll-a retrieval in oceanic waters. Further comparison with other inversion methods demonstrated the relative performance of the new model, especially in productive and algal bloom-dominated waters. To illustrate the use of the new model for remote sensing applications, it was applied to both multispectral Moderate Resolution Imaging Spectroradiometer- Aqua and hyperspectral (Hyperspectral Imager for the Coastal Ocean) images from the algal bloom-dominated waters of the Arabian Sea and turbid productive lagoon waters on the coastal region of the Bay of Bengal. The results were interesting, i.e., the existence of strong spectral features and inflections in the phytoplankton backscattering spectra in bloom-dominated waters and the nearly featureless NAP backscattering spectra varying approximately according to a power law in sedimentladen waters. Corroborating the previous experimental and theoretical studies, our results for algal bloom waters show a steep slope in the blue region and enhanced backscattering in the green and near-infrared regions due to the infl...