Experimental distributive fluvial systems: Bridging the gap between river and rock record

Abstract

A debate has called into question as to which fluvial channel patterns are most widely represented in the stratigraphic record, with some advocating that distributive fluvial systems (DFS) predominate and others that a broad diversity of fluvial styles may become preserved. Critical to both sides is the adequate recognition of original channel planform from geological outcrops separated from their formative processes by millions or even billions of years. In this study the river and rock record are linked through experimentally created DFSs with both aggrading channel beds and floodplains. This approach allows depositing processes and deposited strata to be studied in tandem. Proximal areas comprise coarse, amalgamated channel‐fills with scarce fine‐grained floodplain material. The overall spread of sandbody dimensions become far more varied in medial stretches, with an overall reduction in mean width and depth. In these areas channel‐fills may be sand‐rich or mud‐rich and, following avulsion, all channels are covered by floodplain sediment. Channels, levees and splays form discrete depositional bodies each with varying aspect ratios; a novel breadth of deposits and morphologies in aggrading experiments largely concurrent with proposed trends indicative of DFSs. The proportion of floodplain material increases distally, resulting in decreased interconnectedness of distal channel‐fills. Muddy floodplain sediments significantly change DFSs behaviour and subsequent stratigraphic architecture by enhancing bank stability and reducing avulsion through the filling of floodbasins. The laboratory methods utilised here open up the possibility of controlled experimentation on the effects and mechanisms of DFSs sedimentation, which is important since the modelled stratigraphic trends are rarely so tractable in ancient geological outcrop belts.

Remote sensing of laboratory rivers

“…Sets of neighbouring transects or points are then aggregated into a digital elevation model (DEM). Variations on this laser scanning technique have successfully monitored topography in experiments on landscape evolution (Bonnet & Crave, 2003; Crave et al., 2000; Graveleau & Dominguez, 2008; Lague et al., 2003; Singh et al., 2015), fans and deltas (Chatanantavet & Lamb, 2014; Daniller‐Varghese et al., 2020; Delorme et al., 2017; Finotello et al., 2019; Ganti et al., 2016; Kim & Jerolmack, 2008; Kim & Paola, 2007; Kim, Paola, Swenson, & Voller, 2006; Kim, Paola, Voller & Swenson, 2006; Kim et al., 2010; Martin et al., 2009; Martin et al., 2009; Miller et al., 2019; Piliouras et al., 2017; Reitz & Jerolmack, 2012; Savi et al., 2020; Sheets et al., 2002; Straub et al., 2015; Strong & Paola, 2008; Terwisscha van Scheltinga et al., 2020; Van Heijst & Postma, 2001; Van Heijst et al., 2001), sediment transport (Abramian et al., 2020; Elgueta‐Astaburuaga & Hassan, 2017; Humphries et al., 2012; Madej et al., 2009; Phillips et al., 2018; Stradiotti et al., 2020), channel stability (Johnson et al., 2015; MacKenzie & Eaton, 2017), bed patches, structures and forms (Aberle & Nikora, 2006; Aberle & Smart, 2003; Coleman, 2011; Marion et al., 2003; Nelson et al., 2009, 2010, 2014, 2015; Saletti & Hassan, 2020; Zimmermann et al., 2008, 2010), bar dynamics (Venditti et al., 2012; Wu & Yeh, 2005), channel bend dynamics (Jamieson et al., 2013), bifurcations (Bertoldi & Tubino, 2007), laminar flows (Malverti et al., 2008), biotic inte...…”

“…), and to through‐water surveying by Terwisscha van Scheltinga et al. (2020). Helpful contributions were also made by Mali and Kuiry (2018) and Morgan et al.…”

“…Software and algorithms continue to improve as well, keeping pace with developments in data acquisition. For instance,Terwisscha van Scheltinga et al (2020) benefited from commercial software updates during the course of their through-water photogrammetry experiments, which reduced the likelihood of model 'flipping' in the software. Similarly, new algorithms increase the accuracy of throughwater photogrammetry, such as the machine learning methods ofAgrafiotis et al (2019) or iterative algorithms ofDietrich (2017), which improve on previous methods to correct for refraction at the airwater interface.…”

Stratigraphic forward modelling of distributive fluvial systems based on the Huesca System, Ebro Basin, northern Spain

“…However, outcrops are commonly limited by their lateral extent, and studies of multiple outcrops within the same system are frequently beset with correlation problems that make it difficult to understand the spatiotemporal evolution of the system in detail (Nichols, 1987; Turner et al., 1984). Flume tank experiments have also been used to better understand fluvial sedimentology at a system scale (Connell et al., 2012; Terwisscha van Scheltinga et al., 2020) but have associated scaling issues. Remote sensing, outcrop and flume tank studies can be complemented by numerical models, which can reproduce the behaviour and resultant stratigraphic architecture of fluvial systems at temporal and spatial scale.…”

Spatial variation in the sedimentary architecture of a dryland fluvial system

“…These systems are typically characterized by ephemeral to perennial fluvial discharge, and preserved channel elements with high width‐to‐depth ratios and vertical and lateral connectivity. The preserved deposits of these systems tend to exhibit the following downstream trends: (i) increased dispersal of palaeocurrent directions due to radiating channel patterns from an apex (Owen et al ., 2015); (ii) a decrease in modal grain size due to reduced fluvial discharge with an increase in the proportion of floodplain deposits (Weissmann et al ., 2010, 2013; Owen et al ., 2015); (iii) a decrease in channel element width‐to‐depth ratios due to channel bifurcation and high rates of infiltration and evapotranspiration into the dry substrate (Horton & DeCelles, 2001; Nichols & Fisher, 2007; Weissmann et al ., 2010, 2013; Davidson et al ., 2013; Ventra & Clarke, 2018); and (iv) a decrease in the confinement of channel elements due to a lack of lateral constraints on channel mobility (Weissmann et al ., 2013; Terwisscha van Scheltinga et al ., 2020). Whilst the individual characteristics of this model, when taken in isolation, are true for many types of fluvial system (Sambrook Smith et al ., 2010), a combination of all these characteristics forms a strong basis for an interpretation of the system as an ancient dryland DFS (Terwisscha van Scheltinga et al ., 2020).…”