Mingliang Liu

Based on characteristics analysis about remote sensing reflectance, the Secchi Disk Depth (SDD) in the Qiandao Lake was predicted from the Landsat8/OLI data, and its changing rates on a pixel-by-pixel scale were obtained from satellite remote sensing for the first time. Using 114 matchups data pairs during 2013–2019, the SDD satellite algorithms suitable for the Qiandao Lake were obtained through both the linear regression and machine learning (Support Vector Machine) methods, with remote sensing reflectance (Rrs) at different OLI bands and the ratio of Rrs (Band3) to Rrs (Band2) as model input parameters. Compared with field observations, the mean absolute relative difference and root mean squared error of satellite-derived SDD were within 20% and 1.3 m, respectively. Satellite-derived results revealed that SDD in the Qiandao Lake was high in boreal spring and winter, and reached the lowest in boreal summer, with the annual mean value of about 5 m. Spatially, high SDD was mainly concentrated in the southeast lake area (up to 13 m) close to the dam. The edge and runoff area of the lake were less transparent, with an SDD of less than 4 m. In the past decade (2013–2020), 5.32% of Qiandao Lake witnessed significant (p < 0.05) transparency change: 4.42% raised with a rate of about 0.11 m/year and 0.9% varied with a rate of about −0.09 m/year. Besides, the findings presented here suggested that heavy rainfall would have a continuous impact on the Qiandao Lake SDD. Our research could promote the applications of land observation satellites (such as the Landsat series) in water environment monitoring in inland reservoirs.