Geoscience Reference
In-Depth Information
Bed Load Transport in a Physical Scale Model
of Two Merging Mountain Streams
Sarah Simonett and Volker Weitbrecht
1
Introduction
Modeling bed load transport of a nonuniform grain size distribution in physical
scale models is associated with various problems. The different behaviors of the
grain size fractions mainly in terms of the initial motion (Shields
1936
), the type of
transport such as bed load or suspended load, the effect of cohesion and the
development of bed forms (Simons and Richardson
1996
; Bog´rdi
1974
), might
involve that geometrically scaled model grains feature different characteristics to
nature. The appropriate choice of the model grain size distribution is important for
the accuracy of the test results. Pugh (
2008
), as well as Gill and Pugh (
2009
)
propose a scaling, guaranteeing similitude of particle's settling velocity. Settling
velocity is relevant in determining when a particle will remain at rest or how far it
will travel as suspended load (Pugh
2008
). In the present physical scale model, bed
load transport is the main process. This paper proposes a methodology to simulate
bed load transport in physical scale models minimizing scale effects. It is based on
the correct simulation of initial motion of sediments where the critical shear
velocity is the determining parameter. The methodology is composed of the fol-
lowing changes of the input data: first, conversion of the grain size distribution
(Sect.
3.2
) and secondly, adaptation of the sediment input (Sect.
3.3
) including the
reduction of the sediment input and the extension of the flood hydrograph. A similar
work based on this approach has been conducted by Weitbrecht and Ruther (
2009
).
The herein presented results are motivated by the flood protection project
Meiringen. Meiringen, a mountain village, is situated in the Canton of Bern,
Switzerland, at about 600 m altitude. In August 2005 Meiringen got heavily
flooded by the two lined mountain torrents, Alpbach and Milibach, converging in
