Searching for chaotic dynamics in snowmelt runoff

Chaos analysis has altered the way we view natural systems. Complex or random‐appearing phenomena may be chaotic and thus deterministic, rather than random. In this study, we used the Grassberger‐Procaccia algorithm (GPA) to evaluate a runoff time series from a second‐order catchment in southwestern Idaho for chaotic dynamics. GPA can identify the presence of low‐dimensional 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 random‐appearing behavior of snowmelt runoff is generated from the complex interactions of many factors, rather than low‐dimensional chaotic dynamics.