Experimental evidence for bifurcation angles control on abandoned channel fill geometry

Abstract

Abstract. The nature of abandoned channels' sedimentary fills has a significant influence on the development and evolution of floodplains and ultimately on fluvial reservoir geometry. A control of bifurcation geometry (i.e., bifurcation angle) on channel abandonment dynamics and resulting channel fills, such as sand plugs, has been intuited many times but never quantified. In this study, we present a series of experiments focusing on bedload transport designed to test the conditions for channel abandonment by modifying the bifurcation angle between channels, the flow incidence angles and the differential channel bottom slopes. We find that disconnection is possible in the case of asymmetrical bifurcations with high diversion angle (≥30∘) and quantify for the first time an inverse relationship between diversion angle and sand plug length and volume. The resulting sand plug formation is initiated in the flow separation zone at the external bank of the mouth of the diverted channel. Sedimentation in this zone induces a feedback loop leading to sand plug growth, discharge decrease and eventually to channel disconnection. Finally, the formation processes and final complex architecture of sand plugs are described, allowing for a better understanding of their geometry. Although our setup lacks some of the complexity of natural rivers, our results seem to apply at larger scales. Taken into account, these new data will improve fluvial (reservoir) models by incorporating more realistic topography and grain size description in abandoned channels.

Bedload infilling and depositional patterns in chute cutoffs channels of a gravel‐bed river: The Ain River, France

“…Its downstream end forms a topographic step, a prograding front, over the initial channel bed (Figures 4b, 7a, 12c′ and d′). The observed composite process is close to the one described experimentally by Szewczyk (2020) and Szewczyk et al (2020).…”

“…However, a first bar starts forming just downstream of the bifurcation, in the flow separation zone (Figures 9c and 12b; Constantine et al, 2010). The progressive growth of the bar over time (several years) contributes to further limit the discharge and sediment input in the channel under abandonment (Ashmore, 1991; Ferguson, 1993; Szewczyk et al, 2020; Wheaton et al, 2013). The channel starts narrowing in response to both the plug‐bar construction and the capture of part of the discharge by the chute channel (Figures 9d and e, 12c; Reynolds & Royall, 2020; Sorrells & Royall, 2014).…”

Effect of Lateral Outflow on Three‐Dimensional Flow Structure in a River Delta

“…The flow structures observed in this study are similar to those observed in previous non-discordant diversion studies (Dutta et al, 2017;Herrero et al, 2015;Neary et al, 1999). A shallow elongated bar was observed inside the lateral channel (Figure 3) which is similar to previous observations in non-discordant systems (Bulle, 1926;Herrero et al, 2015;Szewczyk et al, 2020). The reproduction of flow structure and the presence of the shallow bar in the CO study, suggest that the Bulle effect (Bulle, 1926), that is, preferential deviation of bedload sediment into the lateral branch because of the secondary circulation at the mouth, may also take place in discordant lateral channels in deltas gradually filling up the channel.…”

“…According to Michelazzo et al (2016), 3-D eddies form at the mouth of side weirs and act to divert sediment into the weirs. Despite these efforts in open channel hydraulics, there remains a gap between the understanding of flow and transport mechanism from the hydrodynamic models (Dutta et al, 2017) and the more morphology focused studies (Szewczyk et al, 2020) for channelized systems. Moreover, there remains a lack of understanding of how flow structure in discordant systems is modulated by environmental variables such as tides and discharge.…”

A Trade-Off Between Explorations and Repetitions for Estimators of Two Global Sensitivity Indices in Stochastic Models Induced by Probability Measures

“…all we need is a family {Q x } and a probability measure P * . We remark that the above formalism of stochastic models can be used to represent physical models [32] as well.…”