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| Titel |
Streamflow dynamics at the Puget Sound, Washington: application of a surrogate data method |
| VerfasserIn |
N. She, D. Basketfield |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 12, no. 4 ; Nr. 12, no. 4 (2005-05-03), S.461-469 |
| Datensatznummer |
250010671
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| Publikation (Nr.) |
 copernicus.org/npg-12-461-2005.pdf |
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| Zusammenfassung |
| Recent progress in nonlinear dynamic theory has inspired
hydrologists to apply innovative nonlinear time series techniques to the
analysis of streamflow data. However, regardless of the method employed to
analyze streamflow data, the first step should be the identification of
underlying dynamics using one or more methods that could distinguish between
linear and nonlinear, deterministic and stochastic processes from data
itself. In recent years a statistically rigorous framework to test whether
or not the examined time series is generated by a Gaussian (linear) process
undergoing a possibly nonlinear static transform is provided by the method
of surrogate data. The surrogate data, generated to represent the null
hypothesis, are compared to the original data under a nonlinear
discriminating statistic in order to reject or approve the null hypothesis.
In recognition of this tendency, the method of "surrogate data" is applied
herein to determine the underlying linear stochastic or nonlinear
deterministic nature of daily streamflow data observed from the central
basin of Puget Sound, and as applicable, distinguish between the static or
dynamic nonlinearity of the data in question. |
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