Seismic array constraints on reach-scale bedload transport

Abstract

Measurements and mechanical models of heterogeneous bedload transport in rivers remain basic challenges for studies of landscape evolution and watershed management. A 700 m reach of the Trinity River (northern California, USA), a large gravel-bed river, was instrumented with an array of 76 seismographs during a dam-controlled flood and gravel augmentation to investigate the potential for out-ofstream monitoring. The temporal response to gravel augmentation during constant discharge provides strong evidence of seismic sensitivity to bedload transport and aids in identification of the seismic frequencies most sensitive to bedload in the study area. Following gravel augmentations, the seismic array reveals a period of enhanced transport that spans most or all of the reach for ~7-10 h. Neither the duration nor the downstream extent of enhanced transport would have been constrained without the seismic array. Sensitivity to along-stream transport variations is further demonstrated by seismic amplitudes that decrease between the upper and lower halves of the reach consistent with decreased bedload flux constrained by time-lapse bathymetry. Insight into the magnitude of impact energy that reaches the bed is also gained from the seismic array. Observed peak seismic power is ~1%-5% of that predicted by a model of saltation over exposed bedrock. Our results suggest that dissipation of impact energy due to cover effects needs to be considered to seismically constrain bedload transport rates, and that noninvasive constraints from seismology can be used to test and refine mechanical models of bedload transport.

Seismic Tremor Reveals Spatial Organization and Temporal Changes of Subglacial Water System

“…While increased seismic power exists across a broad range of frequencies on Taku Glacier, the strongest power increases composed of polarized, Rayleigh waves fall between 1.5 and 10 Hz (Figure ), which is consistent with the findings of Bartholomaus et al () on Yahtse Glacier, Mendenhall Glacier, Columbia Glacier, and Jakobshavn Isbræ, as well as the tremor frequencies produced by terrestrial rivers (Burtin et al, ; Gimbert et al, ; Schmandt et al, , ; Tsai et al, ). Like the power density spectra in Burtin et al () and Schmandt et al (), glaciohydraulic tremor exhibits as multiple distinct power peaks within this 1.5‐ to 10‐Hz range.…”

“…Seismology has the potential to continuously monitor the evolution of the subglacial water system. Terrestrial rivers and streams produce high‐frequency (>1 Hz) ambient seismic tremor through turbulent water flow and sediment transport, with lower‐frequency tremor signals radiating from turbulent water flow (Burtin et al, ; Gimbert et al, ; Schmandt et al, , ; Tsai et al, ). If bedload transport produces these tremor signals, as hypothesized, the seismic power of a given mechanism of terrestrial river tremor is dependent on the source‐to‐seismometer distance, with seismic tremor sources close to a seismic station (<100 m) recording relatively greater power (Gimbert et al, ; Tsai et al, ).…”

Geomorphic response to gravel augmentation and high‐flow dam release in the Trinity River, California

“…The seismic study design and results are presented in greater detail by Schmandt et al . (). This surrogate technology proved useful for corroborating the results of the conventional transport measurements and extrapolating those transport rates to the reach scale.…”

Seismic signature of turbulence during the 2017 Oroville Dam spillway erosion crisis

“…This challenge was highlighted by Roth et al (2016) and Roth et al (2017), who indicated that the turbulent signal from a waterfall downstream of their study river reach may have dominated the observed lowfrequency signals. Previous studies have attempted to locate the source of fluvial seismic energy by using arrays of seismometers, primarily by observing the variability in seismic amplitudes around the river section of interest (Burtin et al, 5 2011, andSchmandt et al, 2017). A study by Burtin, et al (2010) developed noise correlation function envelopes to identify segments of the Trisuli River that generated the most seismic energy at a given frequency.…”

“…Burtin et al, 2008); natural floods (e.g. Govi, et al, 1993;Hsu, et al, 2011;Burtin et al, 2011;Roth et al, 2016) and controlled floods (Schmandt et al, 2013;Schmandt et al, 2017). In many of these studies, the authors seek to separate the various sources of seismic energy, including 20 precipitation, bedload transport, and flow turbulence (e.g.…”