Temporal scaling in river flow: can it be chaotic?

被引:33
作者
Regonda, SK [1 ]
Sivakumar, B
Jain, A
机构
[1] Univ Colorado, Dept Civil Environm & Architectural Engn, Boulder, CO 80309 USA
[2] Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA
[3] Indian Inst Technol, Dept Civil Engn, Kanpur, Uttar Pradesh, India
来源
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES | 2004年 / 49卷 / 03期
关键词
river flow; scaling; stochastic behaviour; chaotic behaviour; correlation dimension;
D O I
10.1623/hysj.49.3.373.54343
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Identification of the presence of scaling in the river flow process has been a challenging problem in hydrology. Studies conducted thus far have viewed this problem essentially from a stochastic perspective, because the river flow process has traditionally been assumed to be a result of a very large number of variables. However, recent studies employing nonlinear deterministic and chaotic dynamic concepts have reported that the river flow process could also be the outcome of a deterministic system with only a few dominant variables. In the wake of such reports, a preliminary attempt is made in this study to investigate the type of scaling behaviour in the river flow process (i.e. chaotic or stochastic). The investigation is limited only to temporal scaling. Flow data of three different scales (daily, 5-day and 7-day) observed in each of three rivers in the USA: the Kentucky River in Kentucky, the Merced River in California and the Stillaguarnish River in Washington, are analysed. It is assumed that the dynamic behaviour of the river flow process at these individual scales provides clues about the scaling behaviour between these scales. The correlation dimension is used as an indicator to distinguish between chaotic and stochastic behaviours. The results are mixed with regard to the type of flow behaviour at individual scales and, hence, to the type of scaling behaviour, as some data sets show chaotic behaviour while others show stochastic behaviour. They suggest that characterization (chaotic or stochastic) of river flow should be a necessary first step in any scaling study, as it could provide important information on the appropriate approach for data transformation purposes.
引用
收藏
页码:373 / 385
页数:13
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