Indicators of suspended sediment transport dynamics in rivers

• Published in: Hydrology Research Vol. 54; no. 8; pp. 978 - 994
• Main Authors: Shin, Jae hun, Grabowski, Robert C., Holman, Ian
• Format: Journal Article
• Language: English
• Published: London IWA Publishing 01.08.2023
• Subjects: Aquatic ecosystems; box statistics; Catchment area; Climate change; Climate prediction; Cluster analysis; Clustering; Coastal zone; conterminous us; Discharge measurement; Environmental impact; Erosion control; frequency and timing (mft); Gaging stations; Hydrology; Indicators; k-means clustering; magnitude; Mathematical analysis; Mountain regions; Mountainous areas; Rivers; Sediment; Sediment control; Sediment transport; Stream discharge; suspended sediment dynamics indicators; Suspended sediments; Trends; Vector quantization; Hawaii; United States > US; Puerto Rico
• ISSN: 0029-1277; 1998-9563; 2224-7955
• DOI: 10.2166/nh.2023.068

Abstract Suspended sediment (SS) is a natural component of rivers, but elevated SS concentrations (SSCs) can impact aquatic ecosystems and engineering infrastructures. However, a significant gap remains in predicting SSC dynamics, which are influenced by catchment and climate factors that control sediment erosion, transport and deposition. The research aim is to develop and apply new SS transport dynamics indicators to determine how SSC varies spatially and temporally at a continental scale. Daily SSC data (mg/l) from 1,425 gauging stations in the US were used to calculate indicators of magnitude, frequency and timing (MFT). A filtering approach was applied to calculate frequency indicators that capture SSC events of differing durations. Spatial patterns in indicators were examined and integrated using K-means clustering. High SSC was identified at sites in dry and mountainous regions, but longer-duration SSC events were found in the northern US. The western coastal region and Puerto Rico had consistent timings of high SSC (winter and autumn, respectively). SSC magnitude had a decreasing trend over time across most of the US, but increasing trends were identified for the duration of SSC events. The use of MFT indicators is recommended for future studies to support prediction of climate change impacts on SSC.