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| Titel |
Dynamics of monthly rainfall-runoff process at the Gota basin: A search for chaos |
| VerfasserIn |
B. Sivakumar, R. Berndtsson, J. Olsson, K. Jinno, A. Kawamura |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 4, no. 3 ; Nr. 4, no. 3, S.407-417 |
| Datensatznummer |
250001748
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| Publikation (Nr.) |
 copernicus.org/hess-4-407-2000.pdf |
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| Zusammenfassung |
| Sivakumar et al. (2000a), by employing the correlation
dimension method, provided
preliminary evidence of the existence of chaos in the monthly rainfall-runoff
process at the Gota basin in Sweden. The present study verifies and supports the
earlier results and strengthens such evidence. The study analyses the monthly
rainfall, runoff and runoff coefficient series using the nonlinear prediction
method, and the presence of chaos is investigated through an inverse approach,
i.e. identifying chaos from the results of the prediction. The presence of an
optimal embedding dimension (the embedding dimension with the best prediction
accuracy) for each of the three series indicates the existence of chaos in the
rainfall-runoff process, providing additional support to the results obtained
using the correlation dimension method. The reasonably good predictions
achieved, particularly for the runoff series, suggest that the dynamics of the
rainfall-runoff process could be understood from a chaotic perspective. The
predictions are also consistent with the correlation dimension results obtained
in the earlier study, i.e. higher prediction accuracy for series with a lower
dimension and vice-versa, so that the correlation dimension method can indeed be
used as a preliminary indicator of chaos. However, the optimal embedding
dimensions obtained from the prediction method are considerably less than the
minimum dimensions essential to embed the attractor, as obtained by the
correlation dimension method. A possible explanation for this could be the
presence of noise in the series, since the effects of noise at higher embedding
dimensions could be significantly greater than that at lower embedding
dimensions.
Keywords: Rainfall-runoff; runoff coefficient; chaos; phase-space; correlation dimension;
nonlinear prediction; noise |
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