Step–pool formation models and associated step spacing

Abstract

AbstractStep–pool bedforms develop under conditions of high flow rates and high sediment influx and transport rates. Step setting events are capable of mobilizing and rearranging the large step‐forming grain sizes. Thus, observations of the processes of step formation are limited to flume experiments. The results of laboratory experiments involving active transport of widely sorted sediment, including large grains whose deposition readily formed steps, are presented. Over 350 step formations were observed and documented, creating a large data set for detailing and evaluating step formation processes.Existing step‐formation models focus on step development from antidunes, particle clusters, transverse ribs or depositional berms, or from a hydraulic regime that includes cascade flow and hydraulic jumps. These models were developed using field measurements of artificial grade control structures or stable step–pool systems during low flow conditions, or degradational flume experiments where flows elucidated the step–pool bedform in the channel profile but did not create equilibrium transport of the large, step‐forming clasts.This research evaluates the pre‐existing formation models and proposes three new models: the rough bed, exhumation and dune models. The rough bed model was dominant throughout the experiments, followed by the exhumation model and then the dune model. A single model was not responsible for all step formations. The rough bed, exhumation and dune models all influenced step development, and every step sequence was created through a mixture of formation processes. This research generated a large data set, where each step spacing is paired with the corresponding step formation model, making it possible to identify a distinct exclusion zone length for each model. Thus, given knowledge of the step formation model, the minimum distance to the next step downstream can be predicted. From the final spacing of a step sequence, it may be possible to deduce the likely formation mechanisms active during a step resetting event. Copyright © 2007 John Wiley & Sons, Ltd.