 |
| Titel |
Aggregation and sampling in deterministic chaos: implications for chaos identification in hydrological processes |
| VerfasserIn |
J. D. Salas, H. S. Kim, R. Eykholt, P. Burlando, T. R. Green |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1023-5809
|
| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 12, no. 4 ; Nr. 12, no. 4 (2005-06-07), S.557-567 |
| Datensatznummer |
250010679
|
| Publikation (Nr.) |
 copernicus.org/npg-12-557-2005.pdf |
|
|
|
|
|
| Zusammenfassung |
| A review of the literature reveals conflicting results regarding the
existence and inherent nature of chaos in hydrological processes such as
precipitation and streamflow, i.e. whether they are low dimensional chaotic
or stochastic. This issue is examined further in this paper, particularly
the effect that certain types of transformations, such as aggregation and
sampling, may have on the identification of the dynamics of the underlying
system. First, we investigate the dynamics of daily streamflows for two
rivers in Florida, one with strong surface and groundwater storage
contributions and the other with a lesser basin storage contribution. Based
on estimates of the delay time, the delay time window, and the correlation
integral, our results suggest that the river with the stronger basin storage
contribution departs significantly from the behavior of a chaotic system,
while the departure is less significant for the river with the smaller basin
storage contribution. We pose the hypothesis that the chaotic behavior
depicted on continuous precipitation fields or small time-step precipitation
series becomes less identifiable as the aggregation (or sampling) time step
increases. Similarly, because streamflows result from a complex
transformation of precipitation that involves accumulating and routing
excess rainfall throughout the basin and adding surface and groundwater
flows, the end result may be that streamflows at the outlet of the basin
depart from low dimensional chaotic behavior. We also investigate the effect
of aggregation and sampling using series derived from the Lorenz equations
and show that, as the aggregation and sampling scales increase, the chaotic
behavior deteriorates and eventually ceases to show evidence of low
dimensional determinism. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|