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USGS “Did You Feel It?” — Science and lessons from twenty years of citizen science-based macroseismology USGS “Did You Feel It?” — Science and lessons from twenty years of citizen science-based macroseismology

The U.S. Geological Survey (USGS) “Did You Feel It?” (DYFI) system is an automatic method for rapidly collecting macroseismic intensity data from Internet users’ shaking and damage reports and for generating intensity maps immediately following felt earthquakes. DYFI has been in operation for nearly two decades (1999-2019) in the United States, and for nearly 15 years globally. During...
Authors
Vince Quitoriano, David J. Wald

How processing methodologies can distort and bias power spectral density estimates of seismic background noise How processing methodologies can distort and bias power spectral density estimates of seismic background noise

Power spectral density (PSD) estimates are widely used in seismological studies to characterize background noise conditions, assess instrument performance, and study quasi‐stationary signals that are difficult to observe in the time domain. However, these studies often utilize different processing techniques, each of which can inherently bias the resulting PSD estimates. The level of...
Authors
Robert E. Anthony, Adam T. Ringler, David C. Wilson, Manochehr Bahavar, Keith D. Koper

Runoff-initiated post-fire debris flow Western Cascades, Oregon Runoff-initiated post-fire debris flow Western Cascades, Oregon

Wildfires dramatically alter the hydraulics and root reinforcement of soil on forested hillslopes, which can promote the generation of debris flows. In the Pacific Northwest, post-fire shallow landsliding has been well documented and studied, but the potential role of runoff-initiated debris flows is not well understood and only one previous to 2018 had been documented in the region. On...
Authors
Sara Wall, J.J. Roering, Francis K. Rengers

Probabilistic seismic hazard analysis at regional and national scale: State of the art and future challenges Probabilistic seismic hazard analysis at regional and national scale: State of the art and future challenges

Seismic hazard modelling is a multi-disciplinary science that aims to forecast earthquake occurrence and its resultant ground shaking. Such models consist of a probabilistic framework that quantifies uncertainty across a complex system; typically, this includes at least two model components developed from Earth science: seismic-source and ground-motion models. Although there is no...
Authors
M. C. Gerstenberger, W. Marzocchi, T. J. Allen, M. Pagani, Janice Adams, L. Danciu, Edward H. Field, H. Fujiwara, Nico Luco, K-F Ma, C. Meletti, Mark D. Petersen

Earthquakes, ShakeCast Earthquakes, ShakeCast

ShakeCast® – short for ShakeMap Broadcast – is a fully automated software system for delivering specific ShakeMap products to critical users and for triggering established post-earthquake response protocols. ShakeCast is a freely available, postearthquake situational awareness software application that automatically retrieves earthquake shaking data from ShakeMap to compare ground...
Authors
Kuo-wan Lin, David J. Wald, Daniel Slosky

Map depicting susceptibility to landslides triggered by intense rainfall, Puerto Rico Map depicting susceptibility to landslides triggered by intense rainfall, Puerto Rico

Landslides in Puerto Rico range from nuisances to deadly events. Centuries of agricultural and urban modification of the landscape have perturbed many already unstable hillsides on the tropical island. One of the main triggers of mass wasting on the island is the high-intensity rainfall that is associated with tropical atmospheric systems. Puerto Rico’s geographic position and rugged...
Authors
K. Stephen Hughes, William H. Schulz

Evidence for late Quaternary deformation along Crowley's Ridge, New Madrid seismic zone Evidence for late Quaternary deformation along Crowley's Ridge, New Madrid seismic zone

The New Madrid seismic zone has been the source of multiple major (M ~7.0–7.5) earthquakes in the past 2 ka, yet the surface expression of recent deformation remains ambiguous. Crowleys Ridge, a linear ridge trending north‐south for 300+ km through the Mississippi Embayment, has been interpreted as either a fault‐bounded uplift or a nontectonic erosional remnant. New and previously...
Authors
Jessica Thompson Jobe, Ryan D. Gold, Richard W. Briggs, Robert Williams, William J. Stephenson, Jaime E. Delano, Anjana K. Shah, Burke J. Minsley

Geodetic measurements of slow slip events southeast of Parkfield, CA Geodetic measurements of slow slip events southeast of Parkfield, CA

Tremor and low-frequency earthquakes are presumed to be indicative of surrounding slow, aseismic slip that is often below geodetic detection thresholds. This study uses data from borehole seismometers and long-baseline laser strainmeters to observe both the seismic and geodetic signatures of episodic tremor and slip on the Parkfield region of the San Andreas Fault near Cholame, CA. The...
Authors
Brent G. Delbridge, Joshua D. Carmichael, Robert M. Nadeau, David R. Shelly, Roland Burgmann

Operational earthquake forecasting during the 2019 Ridgecrest, California, earthquake sequence with the UCERF3-ETAS model Operational earthquake forecasting during the 2019 Ridgecrest, California, earthquake sequence with the UCERF3-ETAS model

The first Uniform California Earthquake Rupture Forecast, Version 3–epidemic‐type aftershock sequence (UCERF3‐ETAS) aftershock simulations were running on a high‐performance computing cluster within 33 min of the 4 July 2019 M 6.4 Searles Valley earthquake. UCERF3‐ETAS, an extension of the third Uniform California Earthquake Rupture Forecast (UCERF3), is the first comprehensive, fault...
Authors
Kevin R. Milner, Edward H. Field, William H Savran, Morgan T. Page, Thomas H Jordan

A machine learning approach to developing ground motion models from simulated ground motions A machine learning approach to developing ground motion models from simulated ground motions

We use a machine learning approach to build a ground motion model (GMM) from a synthetic database of ground motions extracted from the Southern California CyberShake study. An artificial neural network is used to find the optimal weights that best fit the target data (without overfitting), with input parameters chosen to match that of state-of-the-art GMMs. We validate our synthetic...
Authors
Kyle Withers, Morgan P. Moschetti, Eric M. Thompson

Structural control on megathrust rupture and slip behavior: Insights from the 2016 Mw 7.8 Pedernales Ecuador earthquake Structural control on megathrust rupture and slip behavior: Insights from the 2016 Mw 7.8 Pedernales Ecuador earthquake

The heterogeneous seafloor topography of the Nazca Plate as it enters the Ecuador subduction zone provides an opportunity to document the influence of seafloor roughness on slip behavior and megathrust rupture. The 2016 Mw 7.8 Pedernales Ecuador earthquake was followed by a rich and active postseismic sequence. An internationally coordinated rapid response effort installed a temporary...
Authors
Lillian Soto-Cordero, Anne Meltzer, Eric A. Bergman, Mariah Hoskins, Joshua C. Stachnik, Hans Agurto-Detzel, Alexandra Alvarado, Susan L. Beck, Philippe Charvis, Yvonne Font, Gavin P. Hayes, Stephen Hernandez, Sergio Leon-Rios, Colton Lynner, Jean-Mathieu Nocquet, Marc Regnier, Andreas Rietbrock, Frederique Rolandone, Mario Ruiz

The 2019 Ridgecrest, California, earthquake sequence ground motions: Processed records and derived intensity metrics The 2019 Ridgecrest, California, earthquake sequence ground motions: Processed records and derived intensity metrics

Following the 2019 Ridgecrest, California, earthquake sequence, we compiled ground‐motion records from multiple data centers and processed these records using newly developed ground‐motion processing software that performs quality assurance checks, performs standard time series processing steps, and computes a wide range of ground‐motion metrics. In addition, we compute station and...
Authors
John Rekoske, Eric M. Thompson, Morgan P. Moschetti, Mike Hearne, Brad T. Aagaard, Grace Alexandra Parker
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