Evaluation of two semi-analytical algorithms for retrieving absorption properties in the marginal seas of China: a perspective from water types and trophic levels

Based on a relatively large dataset having concurrent measurements of remote sensing reflectance (<i>R</i>_rs) and absorption coefficients collected in the marginal seas of China (MSC) over the past two decades (2003-2021), we evaluated two widely used semi-analytical algorithms (SAAs) for retrieving the absorption properties in the MSC from both field-measured and satellite data. The SAAs are the quasi-analytical algorithm version 6 (QAA_v6) and the generalized inherent optical properties model (GIOP), while the satellite data are from the moderate resolution imaging spectroradiometer on the aqua satellite. The water body was classified following a proposed system, also separated via the trophic level (oligotrophic, mesotrophic, and eutrophic) based on chlorophyll-a concentration, so the performance of these two SAAs was evaluated for the different water types. For the water types we evaluated, both QAA_v6 and GIOP are found to have different applicable water types in retrieving absorption properties, and the relatively reliable retrieval results of absorption properties are mainly in the water types 3-13, and at the wavebands shorter than 500 nm. In addition, the retrieval performance of these two SAAs for <i>a</i>_dg (the sum of colored dissolved organic matter and non-pigmented particulate matter) and <i>a</i>_ph (phytoplankton pigment) in the eutrophic waters in the MSC still needs to be improved. Before 500 nm, MODIS-Aqua data can provide reliable <i>a</i>_nw (non-water absorption), <i>a</i>_dg, and <i>a</i>_ph with QAA_v6; and can provide reliable <i>a</i>_nw and <i>a</i>_ph with GIOP. This study provides what we believe to be a new and more detailed perspective for evaluating the retrieval of absorption properties using these two SAAs in the MSC, and our results suggest that water types should be considered in improving the estimation of intermediate variables in these SAAs.