Suspended sediment transport in rivers: new indicators of transport dynamics for analysis of catchment and climate controls

Suspended sediment is found naturally in rivers but can cause environmental and engineering problems, especially if the quantity or quality has been altered. Many factors affect suspended sediment concentration (SSC), such as land cover, land use, vegetation growth, and weather, making it difficult to predict changes in SSC at a location over short time periods (e.g., days to months). The aim of this research was to improve the scientific understanding of intra-annual variations in SSC through the statistical analysis of SSC timeseries data from rivers across a variety of catchment and climate characteristics. The specific objectives were to: (i) characterise the continental scale spatio-temporal variations in SSC dynamics using new transport indicators, (ii) determine the contribution of climate to these variations, and (iii) identify SS transport dynamic responses to climate oscillations as a means to separate out the effects of shifts in seasonal weather from catchment influences. The study used daily SSC (mg/l) and site attribute data from the US Geological Survey (USGS), which included 1,666 gauging stations of SSC across the continent, Hawaii and Puerto Rico. First, new indicators of SSC dynamics were developed and applied to the data, based on magnitude, frequency and timing (MFT). Through statistical analysis e.g., principal component analysis (PCA) and K-means clustering, new insights in spatial variability of temporal dynamics in SSC were identified e.g., high extreme events in desert and mountainous areas, the longest duration of events in upper Midwest and distinctly different timing of events in Puerto Rico. Next, further statistical analyses (regression and geographically weighted regression) were conducted on a reduced number of sites (n=120) to determine the relative importance of different catchment and climate factors. The MFT indicators of SS enabled identification of short term dynamics and new understandings of varying influence of land use and land cover. The key results were identified that agricultural covers were positively related with low frequency SSC events. Urban and forest covers brought higher frequency events, except in the driest region. Annual average precipitation had a negative relationship with SSC magnitude. Finally, the influence of climate oscillations e.g., El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO) on SSC transport dynamic indicators was evaluated for four catchments using continuous and cross wavelet analyses. Periodicities in SSC indicators were identified that match climate oscillations, suggesting that small shifts in seasonal weather (e.g., wetter winters) can cause significant changes in SS transport dynamics in rivers. Future works remain to be using latest SS data in the future or application of latest technology e.g., turbidity as well as optimization of input parameters in modelling by generation of MFT time series. This research provides new understandings of SS transport dynamics in rivers and the relative importance of catchment and climatic factors, which will inform practitioners of SS modelling for better predictability in a changing climate.