Articles | Volume 3, issue 3
Research article
13 Jul 2015
Research article |  | 13 Jul 2015

Bedload transport controls bedrock erosion under sediment-starved conditions

A. R. Beer and J. M. Turowski

Abstract. Fluvial bedrock incision constrains the pace of mountainous landscape evolution. Bedrock erosion processes have been described with incision models that are widely applied in river-reach and catchment-scale studies. However, so far no linked field data set at the process scale had been published that permits the assessment of model plausibility and accuracy. Here, we evaluate the predictive power of various incision models using independent data on hydraulics, bedload transport and erosion recorded on an artificial bedrock slab installed in a steep bedrock stream section for a single bedload transport event. The influence of transported bedload on the erosion rate (the "tools effect") is shown to be dominant, while other sediment effects are of minor importance. Hence, a simple temporally distributed incision model, in which erosion rate is proportional to bedload transport rate, is proposed for transient local studies under detachment-limited conditions. This model can be site-calibrated with temporally lumped bedload and erosion data and its applicability can be assessed by visual inspection of the study site. For the event at hand, basic discharge-based models, such as derivatives of the stream power model family, are adequate to reproduce the overall trend of the observed erosion rate. This may be relevant for long-term studies of landscape evolution without specific interest in transient local behavior. However, it remains to be seen whether the same model calibration can reliably predict erosion in future events.

Short summary
We applied a spatiotemporally highly resolved dataset of discharge, sediment transport and bedrock erosion data to assess the validity of landscape evolution models at the process scale (resolution of square meters and minutes). The tools effect is found to be the dominant driver of erosion and an easy model is able to predict measured erosion. For larger scales common discharge-dependend modeling with a discharge threshold is adequate to regive the overal trend of the erosion signal.