## 3 Results  
### TSS Model  
#### 3.1.1 TSS Model Calibration and Validation  
As shown in Table 1, the ranges of the TSS data in the Poyang Lake and Hedi Reservoir datasets were similar, whereas TSS and their mean value in Poyang Lake datasets displayed a higher mean value. Therefore, considering the statistical characteristics of the TSS datasets and the wide applicability of the TSS model, this study used all the datasets from different regions to calibrate and validate the TSS remote sensing estimation model. The aggregated data (a total of 49 pairs of valid data) were divided into two datasets, among which 34 pairs (approximately 70% of the total number of samples) were used to calibrate the TSS retrieval model and the rest of the dataset (15 samples, approximately 30% of the total number of samples) contained the validation data. According to the method in Section 2.3.1, the empirical band ratio and three-band retrieval models with the highest coefficient of determination were obtained through regression analysis among different band combination forms that estimate the TSS concentration. The band ratio and three-band retrieval models are as follows:  
\[\text{TSS}=172.191\times\ln^{2}[R_{rs}(b3)/R_{rs}(b4)]-190.809\ln[R_{rs}(b3)/R_{ rs}(b4)]+61.6 \tag{10}\]  
\[\text{TSS}=-16.517\times\ln[[R_{rs}{}^{-1}(b_{4})-R_{rs}{}^{-1}(b_{3})]R_{rs}(b _{2})]-8.363 \tag{11}\]  
where \(R_{rs}(b_{2})\), \(R_{rs}(b_{3})\) and \(R_{rs}(b_{4})\) represent the reflectance of OLI data in the blue band, green band and red band, respectively. The unit of TSS concentration is in mg/L. Figure 2 shows the different TSS retrieval models based on the best combination of band reflectance, where (a) is the band ratio model and (b) is the three-band model. At the same time, this study also compares the measured TSS values with the predicted values by different models and draws a scatter plot (as shown in Figure 2c,d). Figure 2: The calibration and validation of the TSS remote sensing estimation model between simulated OLI-based \(R_{rs}\) and in situ measurement data are shown in the figure, where (**a**) shows the model calibrated by the band ratio algorithm, and (**b**) shows the model of the three-band algorithm. Plots of measured vs. model-estimated TSS in Hedi Reservoir with a 1:1 fit line (red dotted line), where (**c**) is the result of validating the band ratio model, and (**d**) is the validation result of the three-band model. For the term of the two retrieval models, we find the best regression relationship between simulated OLI-derived \(Ln(R_{rs}(b_{3})/R_{rs}(b_{4}))\) or \(Ln((R_{rs}{}^{-1}(b_{4})-R_{rs}{}^{-1}(b_{3}))R_{rs}(b_{2}))\) and measured TSS data with a higher coefficient of determination (0.849 in the band ratio model and 0.816 in the three-band model). The results show that the two models have a better performance, where \(R^{2}\) is 0.849 and 0.816, respectively, indicating that both models can be used to estimate the TSS concentration in this study area. The \(RMSE\) of the three-band model is 6.243 mg/L, which is 2.31% lower than the 6.391 mg/L of the band ratio model. The \(MRE\) of the three-band model (19.626%) is smaller than the band ratio model (18.027%), and both are less than 20%. Although the determination coefficient of the band ratio model is 4% higher than that of the three-band model, the validation of the band ratio model is higher than that of the three-band model. The \(RMSE\) of the band ratio model is 0.148 mg/L higher than that of the three-band model, and the \(MRE\) has increased by 8.87%. At the same time, the scatter plots of the TSS estimated and the actual values of TSS are well distributed around the 1:1 line. Generally speaking, using the first-order three-band model (as in Equation (11)) for Hedi Reservoir simplified the simulation of the model calibration and validation (\(R^{2}=0.816,RMSE=6.243\text{mg}/\text{L},MRE=18.027\%\)) compared to the second-order band ratio model (as in Equation (10), \(R^{2}=0.849,RMSE=6.291\text{mg}/\text{L},MRE=19.626\%\)) with similar performance.