Earthquake Science Center Seminars

Elnaz Seylabi, University of Nevada, Reno

We perform a series of large scale, nonlinear, earthquake ground motion simulations that account for the cyclic plastic behavior of sediments in the shallow crust. Our goal is to understand and quantitatively assess how idealized models of sediment nonlinearity influence the amplitude, frequency content, and duration of strong ground motion in broadband earthquake simulations. We use the Garner Valley region in southern California as a test case where near-surface nonlinearity has been reported for peak ground accelerations (PGAs) as small as 0.05-0.2g. We model the sediment cyclic response using a multi-axial constitutive model formulated within the framework of bounding surface plasticity in terms of total stress and implemented in a high-performance computing finite element code. We first describe a series of numerical experiments designed to verify our model implementation, and then present a series of idealized large-scale simulations where material properties were extracted from the Southern California Earthquake Center (SCEC) Community Velocity Model CVM-S4.26 (using its optional geotechnical layer). The modulus reduction curves and ultimate shear strength were selected empirically to constrain the nonlinear soil model parameters. Furthermore, we simulate the rupture of the 2010 Mw 5.4 Borrego Springs and a Mw 6.5 scenario earthquakes using a kinematic earthquake rupture model. Having the rupture simulations, we then compute synthetic ground motions with the nonlinear model (for a maximum frequency of 5 Hz) and discuss how modeling shallow crust nonlinearity affects the ground response intensity measures in the different cases considered.

Gabe Paris, University of Alaska Fairbanks AEC

Forecasting how many earthquakes will occur following a potentially damaging earthquake helps the public and emergency operators stay safe and make informed decisions. The USGS issues aftershock forecasts following potentially damaging mainshocks in the U.S. states and territories and updates these forecasts 75 times during the first year. Most of the forecasts are issued automatically, but some forecasts require manual intervention to maintain accuracy. To help identify the sequences whose forecasts will benefit from a modified approach, we built the oaftools R package. Oaftools includes functions that analyze and plot earthquake sequences and their forecasts, and the Operational Aftershock Forecast (OAF) Viewer, which incorporates the functions into an interactive web environment that can be used to explore aftershock sequences. The OAF Viewer displays two maps, one of the mainshocks and one of a sequence's aftershocks, and five analytical plots. The OAF Viewer will help seismologists understand complexities in the data, communicate with the public and emergency managers, and improve the OAF system by maintaining operational awareness. It will also help researchers study aftershock forecasting using their own methods. I used the OAF Viewer to study aftershock forecasting for sequences along the forearc of the Alaskan subduction zone. The USGS considers the forecast to be "successful" when the number of earthquakes observed within the forecasted duration period is within the 95% confidence interval. In the Alaskan forearc, the observed number of earthquakes consistently lie within this broad range of "success," however the forecasts systematically over-predict the number of aftershocks. I analyzed seventeen earthquake sequences in the Alaska forearc region and have developed a set of parameters that may improve early-sequence aftershock forecasting in the region. I stacked the 17 sequences and used maximum likelihood estimation to determine the new parameters and their uncertainty. Following the lessons of Page et al. (BSSA, 2016), I combined the inter-sequence variability and the uncertainty of the parameters from the stacked sequences to produce the total standard deviation for a new forecast model.

Max Schneider, USGS ESC

Public communication for a region’s seismic hazard and aftershock forecasts is often done using maps. But the public products released by scientists are not always built with best practices in visualization or cartography, nor are they empirically validated with rigorous user experiments. In this talk, I will present several projects that investigate how different visualization approaches can affect public understanding of seismic hazard and aftershock risk. First, I consider how seismic hazard can be mapped to comply with research-backed best practices in color selection, legend design and classification of the continuous hazard distribution onto a discrete color map. I apply these best practices to redesign the German seismic hazard map and evaluate it against the original map in a controlled user experiment. The redesigned map improves perception of key principles of hazard, including that it is not spatially concentrated only around areas with previous earthquakes. Next, I evaluate the effectiveness of three techniques for displaying the uncertainty in aftershock forecast maps. In an experiment, participants perform a comparative judgment task, which measures whether a visualization can succeed in reaching two key communication goals: indicating where an aftershock is either highly likely or highly unlikely (“sure bets”) and where the forecast is low but the uncertainty is high enough to imply potential risk (“potential surprises”). All visualizations perform equally well in the goal of communicating “sure bet’’ situations. But the visualization that shows uncertainty using lower and upper bounds significantly outperforms the others at communicating “potential surprises.” I conclude with an outlook on my postdoctoral research on creating and testing visual products for aftershock forecasting at the USGS.

Marius Isken and Sebastian Heimann, GFZ Potsdam and University of Potsdam, Germany

Pyrocko (https://pyrocko.org) is an open source seismology toolbox and library, written in the Python programming language. It can be utilized flexibly for a variety of geophysical tasks, like seismological data processing and analysis, modelling of InSAR, GNSS data and dynamic wave forms, or for seismic source characterization. The presentation introduces the framework and focuses on a flexible and computationally efficient f-k filtering technique for DAS data, which makes use of its dense spatial and temporal sampling, and can handle the large amount of data. The presented adaptive frequency-wavenumber filter suppresses the incoherent seismic noise while amplifying the coherent wave field.

Bio: Marius Paul Isken is a Geophysicist interested in observational seismology and earthquake source characterisation. He studied Geosciences (BSc) and Geophysics (MSc) at the University of Kiel and afterwards worked as a research seismologist at the USGS in Menlo Park and KAUST, Saudi Arabia. Before starting his PhD about distributed acoustic sensing (DAS) for earthquake modelling at the GFZ Potsdam with the section Physics of Earthquakes and Volcanoes in 2020, he worked as a software developer at the University of Kiel (2016 - 2020). In 2018 he co-founded QuakeSaver GmbH, pursuing the aim to develop smart seismometers and seismic networks.

Sabine Loos, Mendenhall Fellow, USGS, NHC

Many data sources that become available after a disaster—such as satellite imagery or reconnaissance surveys—have immense power to inform decisions that influence the trajectory of the affected country for years afterwards. However, often these data sources prioritize specific user groups, easy-to-measure metrics, and short-term understanding. In this talk, I will present on three main examples of designing earthquake information to be more actionable by centering user needs and more equitable by prioritizing vulnerable populations. The first is on developing actionable damage data, in which we identify how different sources of damage data can be applied to post-earthquake decisions to then inform a method to integrate multiple sources of building damage data to be more useful and accurate. The second is on developing post-earthquake data that acknowledges inequities in recovery, a relatively more complex phenomena than damage, looking at how we can integrate data on natural, social, and physical factors to estimate the spatial distribution of populations who will lag during recovery. The third is on current research to improve USGS’s near-real-time earthquake products to be more actionable and equitable, by taking a user-centered approach which combines focus groups with key stakeholders and web analytics to inform updates to current contend and the design of future content. Broadly, evaluating the what, why, and who of earthquake information supports the thoughtful design of future products that are more useful to local planners, reflect the multiple disciplines that study disaster, and, ultimately, inform decisions that lead to more effective and equitable outcomes.

Prof. Estéfan Garcia, Dept. of Civil and Environmental Engineering, Univ. of Michigan

Earthquake surface fault rupture has historically caused significant damage to structures, highways, lifelines, and other critical infrastructure. Field case histories from several large surface fault-rupturing earthquakes have provided valuable insight into the impacts of this hazard on the built environment, but their relative infrequency requires that mechanisms of these hazards be elucidated through supplementary means such as sandbox modeling. In the presented research, numerical models are developed using the discrete element method (DEM) to serve as “virtual experiments” that overcome the physical limitations of traditional sandbox modeling. The advantages of DEM in terms of accurately representing fundamentally discontinuous media and seamlessly capturing large-strain behavior are discussed. The results of DEM simulations of reverse and normal fault rupture are shown to be consistent with past physical studies in terms of the path of fault rupture propagation from bedrock to the ground surface and the manifestation of the resulting fault scarp. Pioneering work on the application of DEM with high-performance computing to surface fault rupture interaction with shallow foundations and in complex site conditions is presented. Finally, guidelines are provided for applying DEM in future studies of surface fault rupture, and potential application to larger scales of regional tectonic deformations over several kilometers are discussed.

Fred Pollitz, USGS ESC Moffett Field

The 15 January, 2022 eruption of Hunga Tonga Hunga Ha’apia is the largest since the 1991 Mount Pinatubo eruption. It produced a local tsunami with up to 15 m height and inundation of 500m; a plume that eventually reached 58 km height; globally recorded infrasound waves through Earth’s atmosphere; acoustic-gravity standing waves at two dominant resonant frequencies; worldwide sea waves driven in part by the atmospheric Lamb pulse. It produced globally observed seismic signals from coupling of the different atmospheric waves with the solid earth, as well as direct signals from the volcano due to the reaction force. We explore different seismological approaches to deriving the source time function of the reaction force, which is well characterized as a sequence of Impulsive vertical forcing that produced seismic wave energy in multiple packets for 5000 s after the initial Surtseyan eruption, with a late burst around 15000 s. The seismological results are consistent with the generation of the eruptive plume that expanded rapidly for the first 90 minutes, implying average forces of 10^12 N over this time but reaching magnitudes as high as 2x10^13 during the eruption subevents.

Kun Wang, Geophysics Group & Center for Nonlinear Studies, LANL

The previous 5 years demonstrate that machine learning is a powerful tool for studying laboratory faults using acoustic emissions (AE) that broadcast from the sliding interface. The AEs can inform us of the instantaneous fault frictional state in shear experiments and also contain information regarding the time remaining to the upcoming laboratory earthquake

Alba Rodríguez Padilla, University of California, Davis

The past vicennial has witnessed four multi-fault, surface rupturing earthquakes in the Eastern California Shear Zone that left behind impressive footprints of widespread deformation in the desert. Inelastic processes from earthquakes contribute to the formation of fault damage zones that constitute a permanent sink of strain energy, modify the elastic properties of the shallow crust and amplify near-field ground shaking. Constraints on the extent of inelastic deformation differ depending on the dataset and methodology used. We combine fracture, strain, and aftershock maps from the Ridgecrest events, and fracture maps from the Landers, Hector Mine, and El Mayor Cucapah earthquakes to reconcile the properties of damage zones across different spatial scales and resolutions. Our observations reveal how macroscopic fracturing generates intense near-fault damage and that widespread damage accrues regionally over multiple earthquake cycles. To the east, the San Andreas and the San Jacinto faults come together in a releasing step-over at Cajon Pass, north of Los Angeles, where the record of multi-fault earthquakes through this junction has long been erased from the surface. Through paleoseismic trenching and finite-element modeling of secondary fault slip, we provide constraints on the frequency and mechanics of past multi-fault earthquakes at this location. Comparison of our record to independent chronologies shows that 20%–23% of earthquakes on the San Andreas and the San Jacinto faults are co-ruptures through Cajon Pass.

Kathryn Materna, Morgan Page, Lisa Schleicher, USGS ESC

We will have a selection of three talks from speakers at SSA:

Kathryn Materna - Determining strain rates and their epistemic uncertainties: Application to Southern California

Morgan Page - Finding the Next Layer of Seismicity Patterns in High-resolution Catalogs

Lisa Schleicher - Identifying Strong-motion Instrument Metadata Inconsistencies Before and After Earthquakes