“Remote sensing inversion technology provides an efficient means for monitoring suspended sediment concentration (SSC), but its applicability to SSC in high concentration and wide range rivers urgently needs to be verified. The research team has constructed a machine learning model based on cross validation recursive feature elimination random forest, which uses Sentinel-2 satellite remote sensing to invert high concentration suspended sediment in the main stream of the Yellow River. This model can be used to quantitatively invert high concentration wide range SSC and estimate the spatial distribution of SSC in river sections, providing technical reference for automatic monitoring methods of SSC in high content sand rivers.”