## Materials and Methods
### Satellite Image Acquisition and Pre-Processing  
Twenty four scenes of Sentinel-3A-OLCI Level-1B data over Lake Taihu from November 2016 to April 2017 with minimal or no cloud cover were chosen and downloaded from the European Space Agency Copernicus Open Access Hub (previously known as the Sentinels Scientific Data Hub; [[https://scihub.copernicus.eu/](https://scihub.copernicus.eu/)]([https://scihub.copernicus.eu/](https://scihub.copernicus.eu/))). The OLCI Level-1B products include top-of-atmosphere (TOA) radiances for the 21 OLCI spectral bands, geolocation information, meteorological variables (e.g., total column water vapor and total columnar ozone), geographical information, and angles. Terra-MODIS Level-1A images captured on the same date as the OLCI data were download from the NASA Ocean Color website ([[http://oceancolor.gsfc.nasa.gov/](http://oceancolor.gsfc.nasa.gov/)]([http://oceancolor.gsfc.nasa.gov/](http://oceancolor.gsfc.nasa.gov/))). Terra-MODIS data were used to take advantage of its near identical transit time over the study area, with respect to Aqua-MODIS, despite its lower-quality (e.g., radiometric quality and striping noise). Terra-MODIS Level-1A data were processed using SeaDAS 7.3 to generate Level-1B data. The satellite Level-1B data were processed in several steps (Figure 2).  
Atmospheric correction: The Sentinel-3A OCLI Level 2 data are not used in this study since there are only \(R_{\rm rs}\) products released in July 2017 and beyond. Also, the \(R_{\rm rs}\) obtained by the SNAP C2 RCC processor, when originally made available, did not provide a sufficiently high accuracy in Lake Taihu and was therefore not used. Instead, the Second Simulation of the Satellite Signal in the Solar Spectrum correction scheme (6S model) [45] was used to obtain \(R_{\rm rs}\) from the Sentinel-3A-OLCI data over Lake Taihu. Many previous studies have shown that the results of the 6S model are more accurate and efficient than those of other calibration models over extremely turbid water [46; 47]. The mid-latitude atmosphere model and continental aerosol model were adopted. The aerosol optical depth (AOD) data measured at the Taihu site using a CE318 Sunphotometer were obtained from AERONET (AErosol RObotic NETwork, [[https://aeronet.gsfc.nasa.gov/](https://aeronet.gsfc.nasa.gov/)]([https://aeronet.gsfc.nasa.gov/](https://aeronet.gsfc.nasa.gov/))). The AERONET data include the AOD at 340, 380, 440, 500, 675, 870, 1020, and 1640 nm, the Angstrom exponent, and the columnar water vapor. The AOD at 550 nm (required as an input to the 6S model) was calculated from the measured AOD and Angstrom exponent.  
Cloud and algal blooms mask: Due to thick aerosols and floating algae, the application of several existing cloud detection algorithms did not lead to acceptable results [48; 49; 34]. Thus, regions with clouds were manually outlined and masked. The floating algae index (FAI) [48] was calculated first, and the algae pixel-growing algorithm (APA) [50] was used to obtain the algal bloom coverage, which was used to mask the algal bloom areas.  
Satellite-in situ comparison: To maximize the number of possible matching pairs between the in situ and satellite observations without compromising quality, the acceptable time interval was relaxed to 6 h instead of the commonly used 3 h time interval. A spatial homogeneity test was then applied to the satellite data [51]; the test required half of the pixels in the 3 \(\times\) 3 window centered around the in situ stations to have valid data, and the variance limit for these valid pixels was <10%. Note that there are a total of 40 matchups obtained in November 2016, March 2017, and April 2017 according to the strict criteria.