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

• Published in: International journal of applied earth observation and geoinformation Vol. 134; p. 104209
• Main Authors: Qiu, Zhiqiang, Liu, Dong, Yan, Nuoxiao, Yang, Chen, Chen, Panpan, Zhang, Chenxue, Duan, Hongtao
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2024
• Subjects: Landsat; Sentinel-2; Suspended sediment concentration; Yellow River; Suspended sediment concentration; Sentinel-2; Landsat; Yellow River
• ISSN: 1569-8432
• DOI: 10.1016/j.jag.2024.104209

•A Sentinel-2 algorithm for deriving suspended sediment concentrations was developed.•SSCs derived from Sentinel-2 and Landsat were spatiotemporally consistent.•The Yellow River tributaries showed notable spatiotemporal variability in SSC.•Spatiotemporal coverage of Sentinel-2 improved by 107.15% and 204.08% over Landsat.•Combining Sentinel-2 could boost the observation frequency of rivers by 35.29%. 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.