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Predictability and chaotic nature of daily streamflow

Kumar, Nagesh D and Dhanya, CT (2011) Predictability and chaotic nature of daily streamflow. In: 34 th IAHR World Congress - Balance and Uncertainty, 26 June - 1 July 2011, Brisbane, Australia.

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Official URL: http://civil.iisc.ernet.in/~nagesh/pubs/IAHR1906.p...

Abstract

The predictability of a chaotic series is limited to a few future time steps due to its sensitivity to initial conditions and the exponential divergence of the trajectories. Over the years, streamflow has been considered as a stochastic system in many approaches. In this study, the chaotic nature of daily streamflow is investigated using autocorrelation function, Fourier spectrum, correlation dimension method (Grassberger-Procaccia algorithm) and false nearest neighbor method. Embedding dimensions of 6-7 obtained indicates the possible presence of low-dimensional chaotic behavior. The predictability of the system is estimated by calculating the system’s Lyapunov exponent. A positive maximum Lyapunov exponent of 0.167 indicates that the system is chaotic and unstable with a maximum predictability of only 6 days. These results give a positive indication towards considering streamflow as a low dimensional chaotic system than as a stochastic system.

Item Type: Conference Paper
Additional Information: Copyright of this article belongs to Engineers Australia.
Keywords: Correlation Dimension; Lyapunov Exponent; Nearest Neighbour; Nonlinear Prediction
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Depositing User: Id for Latest eprints
Date Deposited: 21 May 2013 11:33
Last Modified: 21 May 2013 11:33
URI: http://eprints.iisc.ac.in/id/eprint/46367

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