Calculation of bedload transport in Swiss mountain rivers using the model sedFlow: proof of concept

Abstract

Abstract.Fully validated numerical models specifically designed for simulating bedload transport dynamics in mountain streams are rare. In this study, the recently developed modelling tool sedFlow has been applied to simulate bedload transport in the Swiss mountain rivers Kleine Emme and Brenno. It is shown that sedFlow can be used to successfully reproduce observations from historic bedload transport events with plausible parameter set-ups, meaning that calibration parameters are only varied within ranges of uncertainty that have been predetermined either by previous research or by field observations in the simulated study reaches. In the Brenno river, the spatial distribution of total transport volumes has been reproduced with a Nash-Sutcliffe goodness of fit of 0.733; this relatively low value is partially due to anthropogenic extraction of sediment that was not considered. In the Kleine Emme river, the spatial distribution of total transport volumes has been reproduced with a goodness of fit of 0.949. The simulation results shed light on the difficulties that arise with traditional flow-resistance estimation methods when macro-roughness is present. In addition, our results demonstrate that greatly simplified hydraulic routing schemes, such as kinematic wave or uniform discharge approaches, are probably sufficient for a good representation of bedload transport processes in reach-scale simulations of steep mountain streams. The influence of different parameters on simulation results is semi-quantitatively evaluated in a simple sensitivity study. This proof-of-concept study demonstrates the usefulness of sedFlow for a range of practical applications in alpine mountain streams.

sedFlow – a tool for simulating fractional bedload transport and longitudinal profile evolution in mountain streams

“…To ensure this approximation, Eulerian forward approaches require very small time steps, especially for fast processes. This can be problematic when a relatively fast process, such as the routing of water, is combined with a relatively slow process, such as bedload 18 F. U. M. Heimann et al: The bedload transport model sedFlow Heimann et al (2015) transport including bed level adjustments. The water routing requires small time steps and thus calculation times that may be orders of magnitude too long and slow from the perspective of bedload dynamics.…”

“…Heimann et al (2015) have demonstrated that, despite their simplicity, the implemented hydraulic concepts (Fig. 2) appear to be sufficient for a realistic integrated representation of bedload transport processes.…”

“…), this numeric concept might partially compensate the uncertainty in local grain-size distribution data. For a more detailed discussion of this topic see Heimann et al (2015). To the authors' knowledge there are no in-depth studies assessing the influence of different representations of active surface layer dynamics on simulated bedload volumes.…”

“…The model is provided together with its complete source code free of charge under the terms of the GNU General Public License (GPL) (www.wsl.ch/sedFlow). Examples of the application of sedFlow are given in a companion article by Heimann et al (2015). …”

Generation of a Design Flood-Event Scenario for a Mountain River with Intense Sediment Transport

“…These data were used as benchmarks for the simulation. In this way, an attempt was made to overcome the lack of field validation that is frequently a shortcoming in similar studies (e.g., [37,38]). …”