Multiscale characterization of streamflow and suspended sediment concentration data using Hilbert–Huang transform and time dependent intrinsic correlation analysis

Abstract

In this paper, Hilbert–Huang transform method is applied for the characteristic analysis of monthly streamflow and total suspended sediment (TSS) concentration time series from two stations, Basantpur and Tikrapara in Mahanadi basin, India. All the four time series are first decomposed by the complete ensemble empirical mode decomposition with adaptive noise method into different Intrinsic Mode Functions (IMFs) with specific periodicity and the IMFs are subsequently subjected to the Hilbert transform. The multiscale decomposition clearly detected the annual cycle in all the four time series and statistical significance test of the IMF components showed that the annual and inter annual cycles are significant in deciding the variability of the series except for the streamflow of Tikrapara station. The cross correlation analysis found a direct association between streamflow and TSS in most of the time scales except in the residue. Finally, the time dependent intrinsic correlation (TDIC) analysis is employed to find the association between streamflow and TSS in different time scales. The TDIC analysis proved the existence of long range direct correlation between the two series at intra-annual and annual time scales for the data from both of the stations. From TDIC analysis, it is further noticed that the nature of association between streamflow and sediment concentration is not of unique character always but varies with time scales and in time domain and many reversals of associations are observable at inter annual scales. The negative association between streamflow and sediment concentration is more perceptible in the data from Tikrapara station than that from Basantpur and it infers the influence of internal forcing such as human interventions and basin characteristics.