Bedforms are ubiquitous features on alluvial river channels. Bedform deposits—fluvial cross strata— are the fundamental sedimentary structures of the rock record on Earth and Mars. Bedform evolution and preserved cross strata respond to floods; however, it is unclear which flood durations are likely to be represented in bedform evolution and cross strata. To address this, we quantified the structure of autogenic noise in bedform evolution using high-resolution spatiotemporal data from a steady-state, physical experiment of bedform evolution. 

The data herein accompanies the manuscript “Timescales of Autogenic Noise in Bedform Evolution and Fluvial Cross Strata ” by Vamsi Ganti, Madeline M. Kelley, Debsmita Das and Robert C. Mahon. In this manuscript, we quantified the scales of autogenic noise in sediment efflux, bedform evolution, and preserved deposition rates in fluvial cross strata. We accomplish this using a steady-state experiment of bedform evolution and perform spectral analysis of bed elevation, sediment efflux and preserved deposits. We find that bedform-group (quasi-stable collection of bedforms) turnover timescale sets the lower limit for detecting flood signals in bedform evolution, and floods with duration shorter than bedform turnover timescale can be severely degraded in bedform evolution and cross strata.

All data associated with this manuscript were collected from a steady state experiment of bedform evolution at the Experimental Sedimentology Laboratory at UC Santa Barbara. The experiment was conducted in a 15 m-long, 2 m-wide and 1 m-deep sediment and water recirculating flume. Bedforms evolved under a constant flow discharge of 0.28 m3/s and the flow depth varied from 0.35 m to 0.3 m over the 7 m-long test section. We used quartz sand with a median grain size of 0.35 mm as sediment in the experiment. 

We collected two sets of bathymetric data for the spectral and the bedform-tracking analysis. The spanwise extent of these datasets was centered along the flume centerline. For the spectral analysis, we monitored a 32 mm-by-251 mm patch of bed, located at x = 10 m, at a spatial and temporal resolution of 1 mm and 12 s, respectively, for 65 hrs. This was in conjunction with high resolution sediment flux data from weigh pans at the downstream end of the flume. For bedform tracking, we monitored a 7 m-by-251 mm patch, starting at x = 5 m, at a spatial and temporal resolution of 1 mm and 5 mins, respectively, for 14 hrs. We include these datasets here. 

We computed bedform geometry and kinematics using the multi-scale bedform tracking tool from Lee et al., 2021. We constructed stratigraphy from the bathymetric data by stacking time series of bed elevation profiles and clipping away eroded portions after Ganti et al., 2013. We generated discrete time-power spectral densities for bed evolution (12 s interval data), sediment efflux, and preserved deposition rates using a multi-taper method from Huybers & Curry, 2006. To identify the key autogenic timescales in bedform evolution, we analyzed PSD in log-log space and quantified the time period of gradient breaks in PSD using the ‘findchangepts’ function in MATLAB (Griffin et al., 2023).  Refer to the associated manuscript for the references and further details pertaining to the experiments and data analysis techniques.