Evaluation of bedload transport predictions using flow resistance equations to account for macro‐roughness in steep mountain streams

Abstract

[1] Steep mountain streams typically feature macro-roughness elements like boulders, step-pool sequences, and a varying channel width. Flow resistance because of such roughness elements appears to be an important control on bedload transport rates. Many commonly used bedload transport equations overestimate the transport in steep streams by orders of magnitude. Few approaches take into account the typical macro-roughness elements, and systematic tests of these models with field observations are lacking. In the present study several approaches were considered that allow calculating the contribution of macro-roughness elements to flow resistance. These approaches were combined with bedload transport equations and the predictions were compared to field measurements of discharge, transported bedload volumes, and channel characteristics in 13 Swiss mountain streams. The streams have channel slopes ranging from 2% to 19%, and catchment areas of 0.5 to 170 km 2 . For six streams there were time series of sediment yields, mostly measured annually, and for the other seven streams sediment volume estimates were available for large flood events in 2000 and 2005. All tested equation combinations achieved an improvement in bedload prediction compared to a reference equation that was uncorrected for macro-roughness. The prediction accuracy mainly depended on the size and density of the macro-roughness and on flow conditions. The best performance overall was achieved by an empirical approach accounting for macro-roughness, on the basis of an independent data set of flow resistance measurements.

Alluvial cover controlling the width, slope and sinuosity of bedrock channels

“…However, he also included relative roughness as a separate predictor, which is implicitly dependent on slope. If written out explicitly, the dependence on slope should be stronger, with values of n potentially much larger than 2 (see also Nitsche et al, 2011;Schneider et al, 2015). Measured m values are usually much larger than those derived from models.…”

Gravel threshold of motion: a state function of sediment transport disequilibrium?

“…Despite over a century of quantitative study (Gilbert, 1914), it often remains challenging to predict gravel transport rates to much better than an order of magnitude because of the complexity of grain interactions with the flow and the surrounding grains (e.g., Schneider et al, 2015;Nitsche et al, 2011;Rickenmann, 2001;Wilcock and Crowe, 2003;Chen and Stone, 2008). Predictive models for complex systems often derive utility from their simplicity, as is the case with the widely-used Meyer-Peter and Müller (1948) …”

Bedload transport measurements with impact plate geophones in two Austrian mountain streams (Fischbach and Ruetz): system calibration, grain size estimation, and environmental signal pick-up

“…underwater microphones (Barton et al, 2010;Camenen et al, 2012;Rigby et al, 2015). It is well known that bedload transport rates often show very large variability for given flow conditions (Gomez, 1991;Leopold and Emmett, 1997;Ryan and Dixon, 2008;Recking, 2010), and that prediction of (mean) bedload transport rates is still very challenging, particularly for steep and coarse-bedded streams (Bathurst et al, 1987;Nitsche et al, 2011;Schneider et al, 2015Schneider et al, , 2016. For such conditions, direct bedload transport measurements are typically difficult to obtain, or may be impossible to make during high-flow conditions (Gray et al, 2010).…”