## 1 Introduction  
Total suspended solids (TSS) are essential carriers of organic matter such as nitrogen and phosphorus and their movement and migration play a significant role in the process of global material cycling and change [1]. By influencing the distribution of scattered light in the water body, TSS directly control the primary productivity of the water body [2], which in turn affects the transparency and oxygen content of the water body, and exert a decisive part in the aquatic ecological environment. Reservoirs are one of the most important sources of drinking water for human beings. They are rich in biodiversity and play a decisive role in improving and regulating the surrounding ecological environment. At the same time, the spatial and temporal heterogeneity of TSS and the process of resuspension and flocculation also directly affect the morphological dynamics of the reservoir [3,4]. As a result, TSS are essential for understanding the progress of river sediment transport and water quality variation. The reservoir gradually accumulates suspended matter at different water levels, which reduces the water storage capacity of the reservoir and ultimately reduces the effective storage capacity [5]. Therefore, it is particularly important for real-time monitoring and management of the aquatic environment in the reservoir area to reveal the dynamic of TSS. Since the release of the guidance for the river chief system by the General Office of the State Council of China in 2016, the research of TSS in inland water including lakes and reservoirs has been paid more lasting attention, and the associated research has been conducted by a variety of scholars, governments and social communities [6, 7, 8], such as the Rio Tercero reservoir (Cordoba, Argentina) [6], the Mekong and Bassac Rivers [9, 10], the Amazon River [11], Taihu Lake [8, 12], the Yangtze River [13, 14, 15] and the Pearl River [16, 17, 18, 19]. There are many methods used for monitoring the TSS concentration and the spatial and temporal variation assessment, such as hydrological fixed-site monitoring, in situ cruising investigation, physical models, numerical simulation, remote sensing and so on. Fortunately, as a scientific and rapid investigation tool, remote sensing breaks through the time-consuming, tedious and expensive limitations of traditional monitoring technologies, and it has been considered as a superior method with the advantages of wide coverage, periodic revisits and long series of data collection. With the continuous improvement in remote sensing data in spectral, spatial and temporal resolution, the use of different types of remote sensing data for TSS monitoring and evaluation is increasingly accepted and recognized. There are numerous remote sensing data for assessment of TSS including the series of Land Observation Satellite (Landsat) [18, 20, 21, 22], the Moderate Resolution Imaging Spectroradiometer (MODIS) [11, 12, 23, 24, 25], the Geostationary Ocean Color Imager (GOCI) [8, 26, 27], Environment and Disaster Monitoring and Forecasting Small Satellite Constellation (HJ) [28], Medium Resolution Imaging Spectrometer (MERIS) [9] and so on. Among them, due to the high quality, high spatial resolution and inheritance, Landsat has become the most widely used remote sensing sensor in spatiotemporal dynamic analysis. The commonly used TSS retrieval models are divided into empirical models and analytical models. As far as the empirical model is concerned, it does not need to undergo complicated derivation and parameter initialization, and its form is simple with sufficient accuracy, which is highly efficient to use and will continue to be used for a long time in the future. Although many studies use empirical models for TSS estimation from different sensors, there are significant differences in the band selection of single- or multiple-band models [12, 18, 24, 29, 30]. First, the sensitivity of satellite sensors to different concentrations of TSS is different.