Searching for chaotic dynamics in snowmelt runoff
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Chaos analysis has altered the way we view natural systems. Complex or randomappearing phenomena may be chaotic and thus deterministic, rather than random. In this study, we used the GrassbergerProcaccia algorithm (GPA) to evaluate a runoff time series from a secondorder catchment in southwestern Idaho for chaotic dynamics. GPA can identify the presence of lowdimensional chaotic dynamics for experimental time series. A daily runoff record, 8800 days in length, was examined. We found no evidence of chaotic dynamics in snowmelt runoff. Snowmelt runoff measured at a daily time step has a large number of degrees of freedom, which is characteristic of a random rather than chaotic process. These results suggest that the randomappearing behavior of snowmelt runoff is generated from the complex interactions of many factors, rather than lowdimensional chaotic dynamics. This paper is not subject to U.S. copyright. Published in 1991 by the American Geophysical Union.
author list (cited authors)
Wilcox, B. P., Seyfried, M. S., & Matison, T. H.
complete list of authors
Wilcox, Bradford P||Seyfried, Mark S||Matison, Thor H