A phase-space reconstruction approach to prediction of suspended sediment concentration in rivers

Abstract

The use of phase-space reconstruction approach for understanding and predicting suspended sediment concentration dynamics in rivers is investigated. According to this approach, the dynamic changes of the suspended sediment concentration phenomenon are represented by reconstructing (or embedding) the single-dimensional (or variable) suspended sediment concentration series in a multi-dimensional phase-space. After representing the dynamics in the phase-space, a local approximation method is employed for making predictions. The approach is employed for representing and predicting the dynamics of the daily suspended sediment concentration observed in the Mississippi River basin (at St. Louis, MO) in the United States of America. The predicted suspended sediment concentrations are found to be in very good agreement with the observed ones; not only are the major trends well captured but the minor (noisy) fluctuations reasonably preserved as well. The near-accurate predictions indicate the appropriateness of the phase-space reconstruction approach for understanding the suspended sediment concentration phenomenon. The results (i.e. optimal embedding dimension) also reveal that the suspended sediment concentration dynamics are dominantly influenced by three variables, suggesting that the suspended sediment concentration (and other sediment transport related) phenomena could be viewed from a low-dimensional chaotic dynamic perspective.