Naisen Liu

Phosphorus is the most important nutrient associated with lake eutrophication and changes in cyanobacterial blooms, and particulate phosphorus (PP) is the main form of phosphorus found in highly turbid inland waters. Therefore, it is urgent to monitor PP concentrations in inland water bodies. In this study, we take Hongze Lake as the research area and establish a semianalytical model to estimate PP concentrations based on the total particle absorption coefficient (a_p); the mean absolute percentage error (MAPE) and root-mean-square error (RMSE) values, which indicate the model accuracy, were 14.90% and 0.009 mg/L, respectively. In addition, the construction process and parameter selection criteria of the remote sensing-based PP concentration estimation model were derived using remote sensing data obtained at different spectral resolutions. Sentinel 3 Ocean and Land Color Instrument (OLCI) and Landsat 9 Operational Land Imager version 2 (OLI-2) data were selected as representatives to verify the accuracy of the model; compared to these two datasets, the MAPE values of the models were 16.32% and 26.84%, respectively, while the RMSE values were 0.010 mg/L and 0.014 mg/L, respectively. Finally, the models were applied to Sentinel 3 OLCI and Landsat 9 OLI-2 images obtained on 16 January 2022. The results show that the spatiotemporal distributions of PP concentrations in Hongze Lake estimated from these two images were relatively consistent, but the OLI data reflected overestimations and underestimations in some areas. These research results provide a new methodology for estimating PP concentrations through remote sensing methods and help to further improve the accuracy of remotely sensed PP concentration estimations in inland water bodies.

The Hongze Lake is the fourth largest freshwater lake in China and an important lake for the East Route of the South-to-North Water Diversion Project. The water quality of the lake affects social development and the lives of residents. To assess the impacts of environmental changes and human activities on the distribution of the total suspended matter (TSM) in the Hongze Lake, we developed an algorithm that utilizes the near-infrared (NIR) band to estimate TSM based on in situ measurements. The algorithm was applied to Landsat images to derive TSM distribution maps from 1984 to 2019, revealing significant inter-annual, seasonal, and spatial variability. The relationship between TSM, precipitation, and wind speed was analyzed, and we found that: (1) The estimation model of TSM concentration in the Hongze Lake constructed for TM and OLI has a high accuracy, and it can be used to jointly monitor TSM concentration in the Hongze Lake for long-term series; (2) From 1984 to 2019, the concentration of TSM in the Hongze Lake showed a trend of first rising and then falling, with the maximum value in 2010 at 100.18 mg/L mainly caused by sand mining activities. Precipitation and wind speed weakly influence the inter-annual variation of TSM concentration; (3) The concentration of TSM in the Hongze Lake in summer is easily affected by flooding in the Huai River, and the concentration of TSM in other seasons is significantly negatively correlated with precipitation; (4) TSM is highest in the Huaihe Bay, followed by the Lihe Bay and Chengzi Bay. The main reason for this is that the input of the Huaihe Bay flows directly into this lake area and is also the main navigation channel. The results of this study are of great significance for the protection and management of the water environment of the Hongze Lake.