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You are here : eLibrary : IAHR World Congress Proceedings : 34th Congress - Brisbane (2011) : THEME 3: Water and Carbon: Climate Change Impact : Predictability and chaotic nature of daily streamflow
Predictability and chaotic nature of daily streamflow
Author : D. Nagesh Kumar1 , C.T. Dhanya1
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 systemís 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.
File Size : 906,937 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 34th Congress - Brisbane (2011)
Article : THEME 3: Water and Carbon: Climate Change Impact
Date Published : 01/07/2011
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