Length scale of braided river morphology

Abstract

[1] Pool-bar topography in single-channel rivers has a length scale proportional to channel width. In braided rivers confluence-bifurcation units are analogous to pool-bar morphology and, in some cases, develop from initial alternate bars. Consequently, confluence-bifurcation units are expected to have length that scales with the central anabranch width and that constitutes a basic length scale braided channel morphology. This idea was tested using measurements from a physical model of a gravel bed braided river and from aerial photographs of braided rivers. Length (distance from confluence to bifurcation), anabranch width, and confluence angle of confluence-bifurcation units were measured. A simple length scaling is evident across the range of scales; confluence-bifurcation length is 4-5 times the channel width. This scaling is a fundamental element of braided river morphology and suggests that braided patterns are created by processes, and have morphological regularity, similar to pool-bar units of low-sinuosity single-thread rivers.

Swiftness of biomorphodynamics in Lilliput- to Giant-sized rivers and deltas

“…However, the uncertainty of these relations is large because of the underlying uncertainty of hydraulic resistance and bank stability, so that it is conceivable that scale effects appear when more sensitive and accurate hydraulic geometry models are developed in the future. Nevertheless these findings agree in general with empirical relations that show linear scaling of bar spacing with 4-5 times the channel width (e.g., Hundey and Ashmore, 2009). In conclusion, this means that scale effects are absent, so that the bar pattern and bar length relative to channel width in experiments should be the same as that in nature if the channel geometry is the same, which can be tuned experimentally by floodplain formation processes.…”

A pseudo genetic model of coarse braided‐river deposits

“…Derived from physical laws, flow and sediment-transport models have been developed [Fredsøe, 1978;Ashworth et al, 1994;De Serres et al, 1999;Dargahi, 2004;Millar, 2005;Davy and Lague, 2009]. These physically based models, along with cellular automata models [Murray and Paola, 1994;Coulthard et al, 2002;Thomas and Nicholas, 2002], take into account the transport of sediments on the surface topography and sometimes other processes such as avulsion [Jerolmack and Paola, 2007] or the interaction with vegetation [Edwards et al, 1999;Murray and Paola, 2003;Thomas et al, 2007]. They allow us to analyze the evolution of the surface morphology of braided rivers but they do not provide the resulting internal structure and heterogeneity of the subsurface.…”

Technical Note: Semi-automated effective width extraction from time-lapse RGB imagery of a remote, braided Greenlandic river

“…This has led to the use of nonmetric, true color (RGB) digital camera imagery to capture water surfaces as an inexpensive and image-on-demand alternative to satellite and airborne platforms, especially for braided rivers. To calculate hydraulic parameters (e.g., effective width, braiding index, sinuosity, or bed slope elevation), these studies have commonly classified water surfaces within images either manually or by supervised classification (Egozi and Ashmore, 2008;Bertoldi et al, 2009;Hundey and Ashmore, 2009;Ashmore et al, 2011;Welber et al, 2012). Another parameter estimation approach relies on water surface delineation from automatically generated DEMs constructed from stereo imagery and other data sources (Chandler et al, 2002;Ashmore and Sauks, 2006;Bird et al, 2010;Bertoldi et al, 2010).…”

“…Braided rivers in particular typically display a power-law relationship between floodplain inundation area (which can be remotely sensed) and discharge, which has been exploited using satellites, aerial imagery, and terrestrial time-lapse photography (Smith et al, 1996;Smith, 1997;Chandler et al, 2002;Ashmore and Sauks, 2006;Egozi and Ashmore, 2008;Smith and Pavelsky, 2008;Bertoldi et al, 2009;Hundey and Ashmore, 2009;Bertoldi et al, 2010;Bird et al, 2010;Ashmore et al, 2011;Welber et al, 2012;Williams et al, 2013;Young et al, 2015).…”