Analysing complicated systems we must never forget that the extraordinary increase in the rate of progress in our understanding can tell us nothing about the state of our knowledge.
The hydrological system is extremely complex. To get insight into its behaviour and possible future states it is important to assess not only its individual components but also consider their interaction. Studying the hydrological system in its context allows focusing on the inherent patterns of its behaviour and search for external rules of its functioning. Changing climate can alter the seasonality of river flow, increasing the frequency of some patterns and decreasing that of the other, which can be adequately described in probabilistic terms. Dimensionality reduction facilitates to discern the patterns present in high dimensional systems. The approach suggested herein allows studying the dynamics of river flow seasonality patterns in the context of the present hydrological system in terms of the probability density functions of the weight coefficients in the reduced phase space, using Principal Components for dimensionality reduction. The approach is presented on the example of a large sample of monthly runoff series for Scandinavia and France, which gives a possibility to identify some common features in the dynamics of seasonality of river flow across a vast region of Europe.