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| Titel |
Hydrologic system complexity and nonlinear dynamic concepts for a catchment classification framework |
| VerfasserIn |
B. Sivakumar, V. P. Singh |
| 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 ; 16, no. 11 ; Nr. 16, no. 11 (2012-11-08), S.4119-4131 |
| Datensatznummer |
250013562
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| Publikation (Nr.) |
 copernicus.org/hess-16-4119-2012.pdf |
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| Zusammenfassung |
| The absence of a generic modeling framework in hydrology has long been
recognized. With our current practice of developing more and more complex
models for specific individual situations, there is an increasing emphasis
and urgency on this issue. There have been some attempts to provide
guidelines for a catchment classification framework, but research in this
area is still in a state of infancy. To move forward on this classification
framework, identification of an appropriate basis and development of a
suitable methodology for its representation are vital. The present study
argues that hydrologic system complexity is an appropriate basis for this
classification framework and nonlinear dynamic concepts constitute a
suitable methodology. The study employs a popular nonlinear dynamic method
for identification of the level of complexity of streamflow and for its
classification. The correlation dimension method, which has its base on data
reconstruction and nearest neighbor concepts, is applied to monthly
streamflow time series from a large network of 117 gaging stations across 11
states in the western United States (US). The dimensionality of the time
series forms the basis for identification of system complexity and,
accordingly, streamflows are classified into four major categories:
low-dimensional, medium-dimensional, high-dimensional, and unidentifiable.
The dimension estimates show some "homogeneity" in flow complexity within
certain regions of the western US, but there are also strong exceptions. |
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