Can riverside seismic monitoring constrain temporal and spatial variations in bedload transport during a controlled flood of the Trinity River?

Abstract:

To evaluate the utility of riverside seismic monitoring for constraining temporal and spatial variations in coarse bedload transport in gravel-bed rivers we collected seismic data during a dam-controlled flood of the Trinity River in northern California in May 2015. This field area was chosen because the Trinity River Restoration Project conducts extensive monitoring of water and sediment transport, and riverbed morphology to guide management of the river with the goal of improving salmon habitat. Four three component broadband seismometers were collocated with water discharge and bedload physical sampling sites along a ~30 km reach of the Trinity River downstream of the Lewiston Dam. Arrays with 10–80 cable-free vertical component geophones were also deployed at each of the four sites in order to constrain spatial variability and amplitude decay of seismic signals emanating from the river. Nominal inter-station spacing within the geophone arrays was ~30 m. The largest geophone array consisted of 83 nodes along a 700 m reach of the Trinity River with a gravel augmentation site at its upstream end. Initial analyses of the seismic data show that ground velocity power from averaged from ~7 – 90 Hz is correlated with discharge at all sites. The array at the gravel injection site shows greater high frequency (>30 Hz) power at the upstream end where gravel was injected during the release compared to ~300 m downstream, consistent with bedload transport providing a significant source of seismic energy in addition to water discharge. Declining seismic power during a ~3 day plateau at peak discharge when physical sampler data shows decreasing bedload flux provides a further indication that the seismic data are sensitive to bedload transport. We will use the array data to back-project the seismic signals in multiple frequency bands into the channel to create maps of the time-varying spatial intensity of seismic energy production. We hypothesize that the greatest seismic energy production will be correlated with times of greatest bedload flux constrained by physical sampler data and with locations where repeat sonar scans identify the greatest changes in riverbed bathymetry.