Improving the observations of suspended sediment concentrations in rivers from Landsat to Sentinel-2 imagery

Abstract

Yellow River is famous for its exceptionally higher suspended sediment concentrations (SSC), displaying significant spatiotemporal heterogeneity across diverse sections. Although SSC monitoring of the Yellow River and some of its tributaries has been achieved using Landsat data, it remains unclear whether the inclusion of higher spatial resolution satellites can expand the spatiotemporal monitoring capabilities for the Yellow River and most of its tributaries. In this study, we employed Sentinel-2 imagery, offering superior spatiotemporal resolution, to develop a higher-accurate SSC model and quantitatively evaluated its potential to improve the spatiotemporal coverage of SSC monitoring compared to Landsat satellites. For the Yellow River in the Loess Plateau, the optimized Sentinel-2 model exhibited superior accuracy, achieving R² = 0.91, root mean square error of 728.76 mg/L, and unbiased percentage difference of 16.75%. Notably, distinct SSC distribution differences were observed across different rivers, indicating significant spatial heterogeneity (SSC: 0.58 – 3.01 × 10⁵ mg/L). Moreover, Sentinel-2 showed a significant increase in observation frequency and spatial coverage (204.08% and 107.15%, respectively) compared to Landsat. An additional 35.29% increase in observation frequency was achieved through the combined satellite observation method. Furthermore, based on river width statistics, we found that upgrading the spatial resolution from 10 m to 1 m enhanced the coverage of observable river segments in the Loess Plateau by approximately 47.96%, and by about 50.56% globally. This study established a crucial scientific foundation for integrating Sentinel-2 and Landsat, enabling finer-scale monitoring and management of river sediment.