Remote sensing as a support tool to map suspended sediment concentration over extended river reaches

Abstract

Spatiotemporal variations of sediments transported along rivers play a crucial role in a wide spectrum of uses, such as navigation, recreation, habitats or river environmental protection. The advancement in technology has made it possible to use various indirect techniques to study and evaluate the transport of suspended sediment in fluvial environments. To investigate large-scale phenomena, remote sensing is becoming a largely utilized approach, as it allows to combine spatially distributed and local information. The systematic change of suspended sediment concentration (SSC) and dynamic processes controlling sediment transport at a given local scale are often not well known, and generally investigated using reach-specific field information. In this work, SSC maps were created by combining satellite images with local monitoring in situ SSC data, using the Zhijiang-Chenglingji reach of the Changjiang River (China) as a case study, and analyzing how SSC dynamics changed over the period 2016–2023, considering both low- and high-flow events. Multiple relationships between measured SSC and reflectance were selected from the literature and tested. Results show that a combination of Sentinel-2 bands 3,4, and 5 represents the best-performing statistical model (R2 = 0.73) in mapping SSC spatiotemporal variations over an extent of dozens of kilometers. Despite the uncertainties connected to the small amount of data available and the differences between SSC data measured over the vertical and surface reflectance, this application shows the potential of remote sensing in mapping SSC at a large spatial scale, overcoming the limitations of localized field sampling, eventually suggesting a relatively simple approach that could assist water managers in mapping large-scale dynamics of SSC for applications such as navigation, habitat preservation, and hydropower production.