Remote estimation of total phosphorus concentration in the Taihu Lake using a semi-analytical model

Abstract

ABSTRACT Eutrophication is a severe environmental problem in the most inland lakes. Taihu Lake, the third largest freshwater lake in China, is one of the most eutrophic lakes. Increased phosphorus concentration is thought to be the primary cause of water eutrophication. Proper total phosphorus (TP) monitoring is essential to effectively manage eutrophication in the Taihu Lake. In this study, 216 sample points with 172 modelling points and 44 verification points acquired from 5 field experiments in Taihu Lake, a semi-analytical model was established for estimating the TP concentration based on the absorption coefficient, with the mean absolute percentage error (MAPE) and root mean square error (RMSE) as 16.8% and 0.04 mg L−1, respectively. The application of the model on Sentinel-3 Ocean and Land Colour Instrument (OLCI) data proved the suitability of the model for satellite image with the MAPE and RMSE as 28.56% and 0.05 mg L−1. The OLCI derived TP concentration in the Taihu Lake shown the unique temporal and spatial distribution: TP concentration in Zhushan Bay, Meiliang Bay, Gonghu Bay, and the western coastal regions was significantly higher than the eastern, the southern, and the centre areas. The concentration of TP in Taihu Lake was the highest in summer and the lowest in winter. Furthermore, the versatility of this method was validated by applying in the Hongze Lake and Qiandao Lake, which is a water body dominated by inorganic suspended matter and a clean water body in China with the MAPE and RMSE as 24.10%, 19.35% and 0.004 mg L−1, 0.014 mg L−1. The results of this study could provide a reference for future remote sensing estimation of TP concentration and inland water eutrophication researches.