Performance of existing QAAs in Secchi disk depth retrieval in phytoplankton and dissolved organic matter dominated inland waters

Abstract

A semianalytical model developed to estimate the Secchi disk depth (Z(SD)) was used in eutrophic-to-hypereutrophic reservoirs (Ibitinga, Ibi, and Barra Bonita, BB) placed in the cascade system of the Tiete River, Brazil. The model was evaluated using the simulated remote sensing reflectance based on the Ocean and Land Color Instrument/Sentinel-3A and the Operational Land Imager/Landsat-8 from both reservoirs. Three quasianalytical algorithm (QAA) versions (QAA(v5), QAA(M14), and QAA(w16)) were evaluated to derive the absorption and backscattering coefficients, and then used for Z(SD) retrieval. For BB, where the chlorophyll-a concentration exceeded 200 mg m(-3) , the model based on QAA(v5) showed high uncertainties while the QAA(w16), which was originally parameterized for BB showed better performance regarding the Z(SD) retrieval (mean absolute percentage errors-MAPE of 22%). However, QAA(w16) did not perform satisfactorily for Ibi, which is dominated by colored dissolved organic matter (CDOM). For Ibi, QAA(v5) provided the best result with MAPE of 34.60%, followed by QAA(M14) with 34.65%. QAA-based Z(SD) models tend to perform poorly in waters with high concentration of chlorophyll-a possibly due to phytoplankton package effect, whereas the same models may require additional parameterization in waters dominated by CDOM. Landsat-8 data showed significant potential for Z(SD) retrieval in inland waters. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)