Geology topics

Zachary E. Ross

Publications and source records attributed to Zachary E. Ross.

7 recordsLinked to original sources

USGS2023

Fault roughness at seismogenic depths and links to earthquake behavior

Fault geometry affects the initiation, propagation, and cessation of earthquake rupture, as well as, potentially, the statistical behavior of earthquake sequences. We analyze 18,250 (−0.27 < M < 4.4) earthquakes of the 2016–2019 Cahuilla, California, swarm and, for the first time, use these high‐resolution earthquake locations to map, in detail, the roughness across an active fault surface at depth. We find that the strike‐slip fault is 50% rougher in the slip‐perpendicular direction than parallel to slip. 3D mapping of fault roughness at seismogenic depths suggests that roughness varies by a factor of 8 for length scales of 1 km. We observe that the largest earthquake ( M 4.4) occurred where there is significant fault complexity and the highest measured roughness. We also find that b ‐values are weakly positively correlated with fault roughness. Following the largest earthquake, we observe a distinct population of earthquakes with comparatively low b ‐values occurring in an area of high roughness within the rupture area of the M 4.4 earthquake. Finally, we measure roughness at multiple scales and find that the fault is self‐affine with a Hurst exponent of 0.52, consistent with a Brownian surface.

California↗

USGS2021

Evidence for latent crustal fluid injection transients in southern California from long-duration earthquake swarms

Earthquake swarms are manifestations of aseismic driving processes deep in the crust. We examine the spatiotemporal distribution of aseismic processes in Southern California using a 12-years catalog of swarms derived with deep learning algorithms. In a core portion of the plate boundary region, which is not associated with elevated heat flow, we identify 92 long-duration swarms ranging from 6 months to 7 years that constitute 26.4% of the total seismicity. We find that 53% of the swarms exhibit ultra-slow diffusive patterns with propagating backfronts, consistent with expectations for natural fluid injection processes. The chronology of the swarms indicates that the aseismic driving processes were active at all times during 2008–2020. The observations challenge common views about the nature of swarms, which would characterize any one of these sequences as anomalous. The regional prevalence of these sequences suggests that transient fluid injection processes play a key role in crustal fluid transport.

California↗

USGS2020

The normal faulting 2020 Mw5.8 Lone Pine, Eastern California earthquake sequence

The 2020 M w "> M w 5.8 Lone Pine earthquake, the largest earthquake on the Owens Valley fault zone, eastern California, since the nineteenth century, ruptured an extensional stepover in that fault. Owens Valley separates two normal‐faulting regimes, the western margin of the Great basin and the eastern margin of the Sierra Nevada, forming a complex seismotectonic zone, and a possible nascent plate boundary. Foreshocks began on 22 June 2020; the largest M w "> M w 4.7 foreshock occurred at ∼ 6    km "> ∼6 km depth, with primarily normal faulting, followed ∼ 40    hr "> ∼ 40 hr later on 24 June 2020 by an M w "> M w 5.8 mainshock at ∼ 7    km "> ∼ 7 km depth. The sequence caused overlapping ruptures across a ∼ 0.25    km 2 "> ∼0.25 km 2 area, extended to ∼ 4    km 2 "> ∼ 4 km 2 , and culminated in an ∼ 25    km 2 "> ∼25 km 2 aftershock area. The mainshock was predominantly normal faulting, with a strike of 330° (north‐northwest), dipping 60°–65° to the east‐northeast. Comparison of background seismicity and 2020 Ridgecrest aftershock rates showed that this earthquake was not an aftershock of the Ridgecrest mainshock. The M w "> M w M w – m B "> – m B relationship and distribution of ground motions suggest typical rupture speeds. The aftershocks form a north‐northwest‐trending, north‐northeast‐dipping, 5 km long distribution, consistent with the rupture length estimated from analysis of regional waveform data. No surface rupture was reported along the 1872 scarps from the 2020 M w "> M w 5.8 mainshock, although, the dipping rupture zone of the M w "> M w 5.8 mainshock projects to the surface in the general area. The mainshock seismic energy triggered rockfalls at high elevations ( ⁠ > 3.0    km "> > 3.0 km ⁠ ) in the Sierra Nevada, at distances of 8–20 km, and liquefaction along the western edge of Owens Lake. Because there were ∼ 30 % "> ∼ 30 % fewer aftershocks than for an average southern California sequence, the aftershock forecast probabilities were lower than expected. ShakeAlert, the earthquake early warning system, provided first warning within 9.9 s, as well as subsequent updates.

California↗

USGS2020

Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center

Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC operations. Automatic seismic arrival detections made from standard picking methods (e.g., short‐term average/long‐term average [STA/LTA]) are fed to trained neural network models to improve automatic seismic‐arrival (pick) timing and estimate seismic‐arrival phase type and source‐station distances. These additional data are used to improve the capabilities of the NEIC associator. We compile a dataset of 1.3 million seismic‐phase arrivals that represent a globally distributed set of source‐station paths covering a range of phase types, magnitudes, and source distances. We train three separate convolutional neural network models to predict arrival time onset, phase type, and distance. We validate the performance of the trained networks on a subset of our existing dataset and further extend validation by exploring the model performance when applied to NEIC automatic pick data feeds. We show that the information provided by these models can be useful in downstream event processing, specifically in seismic‐phase association, resulting in reduced false associations and improved location estimates.

Seismological Research Letters↗

USGS2020

Introduction to the Special Issue on the 2019 Ridgecrest, California, Earthquake Sequence

No abstract available.

California↗

USGS2018

Induced earthquake families reveal distinctive evolutionary patterns near disposal wells

The timing of events in seismic sequences can provide insights into the physical processes controlling fault slip. In southern Kansas, the rate of earthquakes rose rapidly starting in 2013 following expansion of energy production into the area, demanding the disposal of large volumes of wastewater into deep wells. Seismicity catalogs that are complete to low magnitudes can provide insights into the physical processes that induce seismicity near wastewater disposal. We develop a catalog of over 130,000 earthquakes recorded in southern Kansas from mid‐March 2014 through December 2017 by applying a matched filter algorithm to an original catalog of 5,831 template earthquakes. Detections have nearly identical waveforms to their associated template event and represent slip on nearly co‐located sections of a fault. We select template events with at least 100 associated detections and examine the characteristics of these prolific families of earthquakes. We find that families located close (<10 km) to areas with significant volumes of injected fluids have near‐Poissonian interevent times and the families remain active over longer durations. Families farther from high‐volume injection wells show strong clustering of interevent times and shorter sequence durations. We conclude that increasing pore fluid pressures from nearby disposal of large volumes of wastewater is the primary driver of these long duration episodes, with earthquake‐earthquake interactions driving sequences at greater distance from the wells.

Kansas↗

USGS2017

Aftershocks driven by afterslip and fluid pressure sweeping through a fault-fracture mesh

A variety of physical mechanisms are thought to be responsible for the triggering and spatiotemporal evolution of aftershocks. Here we analyze a vigorous aftershock sequence and postseismic geodetic strain that occurred in the Yuha Desert following the 2010 M w 7.2 El Mayor-Cucapah earthquake. About 155,000 detected aftershocks occurred in a network of orthogonal faults and exhibit features of two distinct mechanisms for aftershock triggering. The earliest aftershocks were likely driven by afterslip that spread away from the main shock with the logarithm of time. A later pulse of aftershocks swept again across the Yuha Desert with square root time dependence and swarm-like behavior; together with local geological evidence for hydrothermalism, these features suggest that the events were driven by fluid diffusion. The observations illustrate how multiple driving mechanisms and the underlying fault structure jointly control the evolution of an aftershock sequence.

Geophysical Research Letters↗