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| Titel |
Toward a practical approach for ergodicity analysis |
| VerfasserIn |
H. Wang, C. Wang, Y. Zhao, X. Lin, C. Yu |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
2198-5634
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics Discussions ; 2, no. 5 ; Nr. 2, no. 5 (2015-09-21), S.1425-1446 |
| Datensatznummer |
250115196
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| Publikation (Nr.) |
 copernicus.org/npgd-2-1425-2015.pdf |
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| Zusammenfassung |
| It is of importance to perform hydrological forecast
using a finite hydrological time series. Most time series analysis
approaches presume a data series to be ergodic without justifying this
assumption. This paper presents a practical approach to analyze the mean
ergodic property of hydrological processes by means of autocorrelation
function evaluation and Augmented Dickey Fuller test, a radial basis
function neural network, and the definition of mean ergodicity. The mean
ergodicity of precipitation processes at the Lanzhou Rain Gauge Station in
the Yellow River basin, the Ankang Rain Gauge Station in Han River, both in
China, and at Newberry, MI, USA are analyzed using the proposed approach.
The results indicate that the precipitations of March, July, and August in
Lanzhou, and of May, June, and August in Ankang have mean ergodicity,
whereas, the precipitation of any other calendar month in these two rain
gauge stations do not have mean ergodicity. The precipitation of February,
May, July, and December in Newberry show ergodic property, although the
precipitation of each month shows a clear increasing or decreasing trend. |
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