Estimating the optical properties of inorganic matter-dominated oligo-to-mesotrophic inland waters

Abstract

Many studies over the years have focused on bio-optical modeling of inland waters to monitor water quality. However, those studies have been conducted mainly in eutrophic and hyper-eutrophic environments dominated by phytoplankton. With the launch of the Ocean and Land Colour Instrument (OLCI)/Sentinel-3A in 2016, a range of bands became available including the 709 nm band recommended for scaling up these bio-optical models for productive inland waters. It was found that one category of existing bio-optical models, the quasi-analytical algorithms (QAAs), when applied to colored dissolved organic matter (CDOM) and detritus-dominated waters, produce large errors. Even after shifting the reference wavelength to 709 nm, the recently re-parameterized QAA versions could not accurately retrieve the inherent optical properties (IOPs) in waterbodies dominated by inorganic matter. In this study, three existing versions of QAA were implemented and proved inefficient for the study site. Therefore, several changes were incorporated into the QAA, starting with the re-parameterization of the empirical steps related to the total absorption coefficient retrieval. The re-parameterized QAA, QAAOMW showed a significant improvement in the mean absolute percentage error (MAPE). MAPE decreased from 58.05% for existing open ocean QAA (QAALv5) to 16.35% for QAAOMW. Considerable improvement was also observed in the estimation of the absorption coefficient of CDOM and detritus from a MAPE of 91.05% for QAALv5 to 18.87% for QAAOMW. The retrieval of the absorption coefficient of phytoplankton (aϕ) using the native form of QAA proved to be inaccurate for the oligo-to-mesotrophic waterbody due to the low aϕ returning negative predictions. Therefore, a novel approach based on the normalized aϕ was adopted to maintain the spectral shape and retrieve positive values, resulting in an improvement of 119% in QAAOMW. Further tuning and scale-up of QAAOMW to OLCI bands will aid in monitoring water resources and associated watershed processes.