Estimating CDOM Concentration in Highly Turbid Estuarine Coastal Waters

We proposed a support vector machine (SVM) algorithm to retrieve colored dissolved organic matter (CDOM) concentration (using ag(443) as a proxy) in the highly turbid Pearl River estuary. Two band ratios, namely, Rrs(443)/Rrs(547) and Rrs(488)/Rrs(547), were used as inputs. Comparisons between the estimated and measured ag(443) illustrated high accuracy of the SVM algorithm, yielding R2s of 0.98 and 0.89, mean absolute percentage errors of 5.18% and 13.1%, and root‐mean‐square deviations of 0.012 and 0.034 m−1 for the training and validation data sets, respectively. The SVM algorithm was also evaluated against existing ones for the study area and gave the best accuracy with a R2 of 0.9, a mean absolute percentage error of 10.23%, and a root‐mean‐square deviation of 0.025 m−1. The diurnal dynamics of CDOM in the Pearl River estuary was revealed showing complicated variations and influenced by the combined effects of wind, tide, circulation, and river discharge. As for remote sensing applications, the SVM‐based CDOM product exhibited great potential to trace the Pearl River plume and the satellite‐derived plume area agreed well with the FVCOM model simulation result. SVM is an accurate and fast tool for retrieving CDOM concentration, especially in highly turbid estuarine coastal waters, and thus, river plume dynamics can be traced. Plain Language Summary Colored dissolved organic matter is an important optically active component in the water column. Together with others, it determines the water color. In this study, we developed an algorithm to retrieve colored dissolved organic matter from remote sensing measurements in the turbid Pearl River estuary. The algorithm performs with high accuracy and outcompetes existing ones. Based on the algorithm, the diurnal dynamics of colored dissolved organic matter and the forcing factors were analyzed. The algorithm was also applied to a satellite scene. The characteristics of the Pearl River plume were elucidated. The result agrees well with that from a numerical model. The approach proposed here has great potential to track river plumes and assist in policy making to protect marine ecosystems. Key Points A SVM algorithm was developed to estimate CDOM in the turbid Pearl River estuary and demonstrated high accuracy Diurnal dynamics of CDOM in the Pearl River estuary was revealed and factors affecting CDOM variations were analyzed Implementation of the SVM algorithm to satellite imagery indicated great potential for pl