Abstract. Self-organization in an experimental braided river is studied. It is shown that the experimental braided river self-organizes into a critical state where it shows dynamic scaling; that is, small and large parts of the river evolve statistically identically after proper renormalization of space and time. The dynamic scaling emerges during the process of approaching the critical state which involves self-adjustment of both profile (vertical selforganization) and braiding pattern (horizontal self-organization). The obtained result corroborates the hypothesis suggested by the authors earlier [Sapozhnikov and FoufoulaGeorgiou, 1997] that braided rivers are self-organized critical systems. The results are also important for understanding and statistically predicting the behavior of natural braided rivers because, owing to external conditions (e.g., sudden streamflow changes), some of them may be driven out of the critical state and therefore may show deviation from dynamic scaling.
IntroductionBraided rivers are complex systems characterized by hierarchical geometry and rapid evolution. Since by definition SOC systems show critical behavior only after they have brought themselves to a critical state, which is also a statistical equilibrium state, Sapozhnikov and FoufoulaGeorgiou [1997] left their experimental braided river to evolve until both its profile and braiding pattern reached equilibrium, and then the presence of SOC was tested. We note here that the profile reached the static equilibrium (i.e., it stopped changing), whereas the braiding pattern, while remaining statistically the same, was undergoing continual changes (statistical equilibrium). After the river reached the equilibrium state we analyzed it for criticality and, indeed, found the presence of dynamic scaling, an indicator of a critical state.However, a more thorough study of a SOC system requires exploration of its behavior not only at equilibrium but also before it reaches this state. Thus, in this study we examine an experimental braided river at different stages, as it approaches statistical equilibrium. There are two motivations for such a study. The first motivation is theoretical. It stems from the fact that critical systems show dynamic scaling at the critical state but deviate from dynamic scaling as they are driven out of this state [e.g., see Ma, 1976]. Therefore, to confirm that a state a system brought itself into is critical, it is important not only to demonstrate the presence of dynamic scaling at this state but also to show that the dynamic scaling was not present before and only arose as the system approached this state. The second motivation stems from the fact that in transferring results from 843