## 4 Discussion
### Performance of the OLCI K\({}_{d}\)(490) Algorithm
#### 4.1.2 Comparison with Existing Algorithms Using the OLCI-Derived \(R_{\text{rs}}\)  
We evaluated the published empirical algorithms proposed by [PERSON] (2017), [PERSON] et al. (2017), and [PERSON] et al. (2018), in addition to a semi-analytical algorithm proposed by [PERSON] et al. (2017) based on satellite-in situ matchups. Due to the significant differences in the bio-optical properties of different waters, we first calibrated the coefficients for these empirical algorithms using the calibration data set from Lake Taihu. The blue-green band ratio (490/560) algorithm commonly used for oceanic waters ([PERSON], 2017) had a relatively low estimation accuracy (R\({}^{2}\) = 0.34, RMSE = 1.88 m\({}^{-1}\), RMSE\({}_{\text{rel}}\) = 47.39%, MNB = 15.89% and NRMS = 45.21%) (Table 2). This is mainly because \(K_{\text{d}}\)(490) for the waters of Lake Taihu is mainly controlled by the SPM in the waters and is insignificantly related to the Chla concentration. The blue-red band ratio (490 nm/620 nm) algorithm suitable for coastal waters ([PERSON], 2017) also had a low estimation accuracy (R\({}^{2}\) = 0.02, RMSE = 2.30 m\({}^{-1}\), RMSE\({}_{\text{rel}}\) = 64.00%, MNB = 25.95% and NRMS = 59.25%). This is mainly because the absorption peak of microcystis aeruginosa, which is the main algal species in Lake Taihu, occurs at 620 nm, so the blue-red band ratio cannot accurately reflect information about the SPM in the waters of Lake Taihu. The red-blue band ratio (674 nm/490 nm) algorithm (K  
\(K_{\rm d}(490)\) for the waters of turbid inland lakes from remote sensing data. The dual band ratio (681 nm/560 nm and 754 nm/560 nm) algorithm developed in this study had a high estimation accuracy (R\({}^{2}\) = 0.81, RMSE = 0.99 m\({}^{-1}\), RMSE\({}_{\rm rel}\) = 25.36%, MNB = 2.81% and NRMS = 25.73%). This is because the NIR, red, and green bands are the key bands for deriving the water quality parameters of inland waters from remote sensing data [25], particularly for deriving Chla and SPM concentrations [55; 56; 57]. The single band ratio (681 nm/560 nm) algorithm also had a relatively high estimation accuracy (R\({}^{2}\) = 0.66, RMSE = 1.32 m\({}^{-1}\), RMSE\({}_{\rm rel}\) = 31.58%, MNB = 6.41% and NRMS = 31.56%). However, large uncertainties were associated with the estimation results obtained using this algorithm for Lake Taihu, which had a wide distribution of algae. Figure 10 shows the estimates of \(K_{\rm d}(490)\) on April 29, 2017 that were obtained using the single band ratio algorithm and the dual band ratio algorithm. The estimates obtained using these two algorithms were generally consistent with one another in areas without algal blooms (mean values of 5.26 \(\pm\) 1.20 and 5.67 \(\pm\) 2.16 m\({}^{-1}\), respectively). However, there was a large difference between the estimates of \(K_{\rm d}(490)\) in algal bloom-covered areas and areas with high algal particle concentrations in the periphery (red circles in Figure 10a). Evidently, the single band ratio algorithm significantly underestimated \(K_{\rm d}(490)\) for algal bloom-covered waters (Figure 10b), whereas the estimates obtained using the dual band ratio algorithm were too high (Figure 10c). The estimates obtained using the dual band ratio algorithm were more consistent with the actual conditions. This is because as the amount of planktonic algae in the water increases, the \(R_{\rm rs}\) value of the water at 560 nm also increases due to the impacts of the low absorption of phytoplankton pigments and scattering by algal cells, whereas the \(R_{\rm rs}\) value of the water at 681 nm decreased as a result of the absorption by Chla [58; 59]; consequently, the 681-nm/560-nm band ratio decreased, which in turn led to an underestimation. Because the reflection of water at 754 nm mainly relies on the SPM concentration and is the least sensitive to algal pigments [60], the effects of changes in the algal concentration can be reduced by using another band ratio (754 nm/560 nm) to compensate for the deficiency in the 681-nm/560-nm band ratio.