Total phosphorus (TP) concentration is a crucial parameter to assess eutrophication in lakes. As one of the most concentrated regions for freshwater lakes, the Yangtze-Huaihe region plays a significant role in monitoring TP concentrations for the sustainable utilisation of China’s water resources. In this study, a TP concentration estimation model suitable for large-sized lake groups was developed using a combination of measured and remote sensing data powered by advanced machine learning algorithms. Compared to traditional empirical models, the model developed in this study demonstrates significant accuracy in fitting (R² = 0.53, RMSE = 0.08 mg/L, MAPE = 34.20%). Moreover, the application of this model to lakes in the Yangtze-Huaihe region from 2017 to 2022 has been conducted. The multi-year average TP concentration was 0.18 mg/L. Spatial distribution analyses showed that total phosphorus concentrations were higher in small lakes. In terms of temporal changes, the interannual decreases in total phosphorus concentrations were 0.02 mg/L, 0.01 mg/L, and 0.01 mg/L for small, medium, and large lakes, respectively. We also found that large lakes typically exhibited a “high in spring and summer, low in autumn and winter” pattern until 2020, but transitioned to a “high in summer and autumn, low in spring and winter” pattern after 2020 due to the removal of closed fish nets, which were having a significant impact on the lake ecosystem. Other lakes in the area consistently showed a pattern of “high in spring and summer, low in autumn and winter” during the six-year period. These findings may provide useful references and suggestions for the environmental protection and management of lakes in China.