Suspended sediment concentration (SSC) is a key indicator of river sediment transport processes and water environmental change. For medium-width rivers, continuous-reach SSC monitoring remains constrained by the spatial discontinuity of station observations and the temporal or consistency limitations of single-source satellite imagery. To improve multi-year SSC characterization in the middle and lower reaches of the Liaohe River, this study integrated Harmonized Landsat and Sentinel-2 (HLS) surface reflectance imagery from 2016 to 2022 with SSC observations from five hydrological stations and developed a random forest retrieval model using multi-band reflectance and sediment-related spectral features. The trained model was applied to valid HLS images to examine SSC spatial distribution, interannual variation, and inter-station reach differences. The model achieved a test-set R2 of 0.641, an RMSE of 0.083 kg·m−3, and an MAE of 0.067 kg·m−3. The median composite of 52 retrieval images showed a lower SSC in the Tieling–Mahushan and Mahushan–Pinganbao reaches and a higher SSC in the Pinganbao–Liaozhong and Liaozhong–Liujianfang reaches. SSC was generally higher in 2016 and 2022 and lower in 2018. These findings indicate that HLS-based retrieval can support continuous-reach SSC monitoring and regional water–sediment dynamic assessment in medium-width rivers, although the accurate quantification of extreme high-SSC events still requires additional in situ samples and higher-frequency observations.
Luan et al. (Fri,) studied this question.