Multiscale Analysis of Water Quality Time Series Data using the Hilbert Huang Transform

ADARSH, S and JANGA, REDDY M (2014) Multiscale Analysis of Water Quality Time Series Data using the Hilbert Huang Transform. In: Second International Conference on Advances In Civil, Structural and Environmental Engineering- ACSEE 2014, 25 - 26 October 2014, Zurich, Switzerland.

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Abstract

This paper presents the multiscale spectral analysis of four water quality time series data from an Indian river. First, the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is employed for multiscale decomposition and the resulted orthogonal modes namely Intrinsic Mode Functions (IMFs) are subsequently subjected to the Normalized Hilbert Transform (NHT). The spectral representation clearly depicts the nonlinearity and non-stationarity of the datasets and the time varying behavior of dominant frequency. The marginal Hilbert spectrum of different parameters shows that the dominant frequency of most of the pollutants is at high frequency range which indicates the significant anthropogenic impacts in the study area. Also the trend analysis performed upon the instantaneous amplitudes show that the high frequency components are responsible for overall trend of the four time series during the study period under consideration. The multiscale decomposition process and the results of spectral analysis may improve the modeling efforts on the river system.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Amplitude, Frequency, Multiscale Decomposition, Hilbert Huang Transform, Water Quality
Depositing User: Mr. John Steve
Date Deposited: 30 May 2019 08:30
Last Modified: 30 May 2019 08:30
URI: http://publications.theired.org/id/eprint/2996

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