Field Application and Validation of a Seismic Bedload Transport Model

Abstract

Bedload transport drives morphological changes in gravel-bed streams and sediment transfer in catchments. The large impact forces associated with bedload motion and its highly dynamic spatiotemporal nature make it difficult to monitor bedload transport in the field. In this study, we revise a physically-based model of bedload-induced seismic ground motion proposed by Tsai et al. (2012, htpps://doi.org/10.1029/2011GL050255) and apply it to invert bedload flux from seismic measurements alongside an Alpine stream. First, we constrain the seismic response of a braided river reach with a simple active experiment using a series of large-rock impacts. This allows the characterization of surface wave propagation and attenuation with distance from the impact source. Second, we distinguish bedload-generated ground vibrations from those caused by turbulent flow using frequency-based scaling relationships between seismic power and discharge. Finally, absolute bedload transport rates are quantified from seismic measurements using inverse modeling based on a simplified formulation of bedload particle motion. The results are verified with a large data set of bedload samples, demonstrating that seismic measurements can provide an indirect measure for bedload flux with uncertainties within a factor of 5 ±1 for instantaneous measurements (between 0.01 and 1 kg/m/s). Larger deviations may be caused by uncertainties in the contribution of turbulent flow effects, particle impact velocity, and especially particle size that may vary with sediment supply and flow conditions. When constraining these uncertainties, instream sediment transport measurements are no longer necessarily required and seismic monitoring may provide an accurate and continuous means to investigate bedload dynamics in gravel-bed streams.

Grain‐Size Distribution and Propagation Effects on Seismic Signals Generated by Bedload Transport

“…However, this still results in a bedload flux overestimation by two orders of magnitude. The Tsai et al ( 2012) model demonstrates strong sensitivity to the coarse tail of the imposed GSD, which is most difficult to measure (e.g., Bakker et al, 2020). From an observational perspective, this may pose a challenge.…”

“…The aim of this study is to constrain the Tsai et al (2012) seismic model with dedicated field experiments and to test it against independent bedload measurements. This approach is similar to that adopted in Bakker et al (2020), although (i) we target a quite different river, the Nahal Eshtemoa in Israel, that has a different geometry (e.g., smaller slope and grain sizes) and experiences different flow conditions, since it is located in a semi-arid region in which water flow only occurs during episodic flash floods, (ii) we make use of a newly implemented code to run the model with discrete, measured grain-size classes, and (iii) we constrain ground seismic properties relevant for the description of wave propagation in the model, using array-based active seismics, as opposed to performing empirical calibration from simpler rock impacts. We exploit hydraulic and bedload flux time series, recorded by a state-of-the-art stream observatory, to invert the seismic data and reconstruct bedload flux, and then compare the results against high-quality independent observations.…”

Using Continuous Turbidity and Seismic Measurements to Unravel Sediment Provenance and Interaction Between Suspended and Bedload Transport in an Alpine Catchment

“…Spectrograms with a 3s temporal resolution were obtained using the method of Welch (1967) and were aggregated to a 10‐min resolution, using a median value to minimize anthropogenic noise. We used the seismic power (P b , m 2 /s 2 ) at a frequency of 50 Hz, providing a maximum sensitivity to bedload transport (Bakker et al., 2020). This frequency range associated with bedload was determined directly by comparing seismic measurements with cross‐section bedload samples and indirectly by scaling discharge (Bakker et al., 2020).…”

“…We used the seismic power (P b , m 2 /s 2 ) at a frequency of 50 Hz, providing a maximum sensitivity to bedload transport (Bakker et al., 2020). This frequency range associated with bedload was determined directly by comparing seismic measurements with cross‐section bedload samples and indirectly by scaling discharge (Bakker et al., 2020). Seismic power caused by bedload transport (P b ) results from impacts exerted by the transported material on the river bed.…”

“…A promising technique to do so consists in near river bed passive seismic monitoring. Recent observations and theoretical considerations suggest that river‐induced seismic ground motion is largely caused by the transport of coarse particles impacting the river bed (Burtin et al., 2008; Gimbert et al., 2014; Tsai et al., 2012), such that the associated bedload transport flux can be inverted from ground‐motion amplitude measurements (Bakker et al., 2020; Dietze et al., 2019; Gimbert et al., 2019; Tsai et al., 2012). More generally, seismic observations may be a particularly relevant proxy for river bed mobility, especially given its strong dependency on the coarsest transported grain sizes (Tsai et al., 2012) whose motion is known to control river bed mobility in gravel bedded streams (MacKenzie et al., 2018; Recking, 2010).…”