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Conference Papers

Browse almost 5,000 conference papers authored by our scientists and refine search by topic, location, year, and advanced search.

Filter Total Items: 5311

Earthquake scenario development in the 2023 USGS NSHM update

Earthquake scenarios are generally selected to serve a wide variety of local and regional needs ranging from testing a community’s ability to respond to earthquakes to developing proactive targeted mitigation strategies for minimizing impending risk. These deterministic scenarios can also be used to communicate seismic hazard and risk to audiences who are not well versed in more complex methods li
Authors
Robert Edward Chase, Kishor S. Jaiswal, Mark D. Petersen

Earthquake scenario selection for portfolio holders in CEUS: A case study with Oklahoma DOT

Portfolio managers of spatially distributed assets in the central and eastern United States (CEUS) and other low- to moderate seismic hazard regions require scenario-based seismic risk assessment for the purpose of emergency management and planning. Uncertainties regarding the long-term seismicity of the region, unknown faults, and limited historical records complicate the selection of an earthqua
Authors
Yolanda C Lin, L. L. Rotche, Kuo-wan Lin, Eric M. Thompson, David Lallemant, W. Peters, David J. Wald

Implementation of basin models and sediment depth terms in the 2023 update of the U.S. National Seismic Hazard Model: Example from Reno, Nevada

We present a framework to evaluate the inclusion of candidate basin depth models in the U.S. Geological Survey National Seismic Hazard Model. We compute intensity measures (peak and spectral amplitudes) from uniformly processed earthquake ground motions in and around the basin of interest and compare these to ground-motion model (GMM) estimates over a range of oscillator periods. The GMMs use dept
Authors
Sean Kamran Ahdi, Morgan P. Moschetti, Brad T. Aagaard, Kaitlyn Abernathy, Oliver S. Boyd, William J. Stephenson

Estimates of kappa in the San Francisco Bay area

Site characterization is a critical component of seismic hazards studies, especially in the development and use of ground motion models (GMMs). One such parameter, kappa (Κ0), represents local site attenuation and effectively describes regional variations in ground motion [1]. However, estimates of Κ0 are limited. We estimate the site parameter Κ0 for 296 broadband and accelerometer stations in th
Authors
Tara A. Nye, Valerie J. Sahakian, E.L. King, Annemarie S. Baltay, Alexis Klimasewski

Earthquake early warning: Toward modeling optimal protective actions

Over the past few years early earthquake warning systems have been incorporated into earthquake preparation efforts in many locations around the globe. These systems provide an excellent opportunity for advanced warning of ground shaking and other hazards associated with earthquakes. This study aims to optimize this advanced warning for individuals inside a building when the alert is received. A c
Authors
M. Wood, X. Zhang, X. Zhao, Sara McBride, Nicolas Luco, D. Baldwin, T. Covas

2018 M7.1 Anchorage and 2021 M7.2 Nippes, Haiti earthquake case studies for Virtual Earthquake Reconnaissance Team (VERT) activation protocols, policies, and procedures to gather earthquake response footage

The collection of online videos and imagery to use in disaster reconnaissance is increasing in frequency, due to accessibility of platforms and the ubiquitous nature of smartphones and recording devices. In this short article, we explore the processes, goals, and utility of Virtual Emergency Reconnaissance Teams (VERTs) to collect footage and imagery of geohazards (earthquakes, volcanoes, tsunamis
Authors
Sara McBride, J. Bellizzi, S. Gin, G. Henry, D. F. Sumy, D. Baldwin, E. Fischer

Integrated strategies for enhanced rapid earthquake shaking, ground failure, and impact estimation employing remotely sensed and ground truth constraints

Estimating earthquake impacts using physical or empirical models is challenging because the three components of loss estimation-shaking, exposure, and vulnerabilities-entail inherent uncertainties. Loss modeling in near-real-time adds additional uncertainties, yet expectations for actionable information with a reasonable level of confidence in the results are real. The modeling approaches describe
Authors
David J. Wald, Susu Xu, H. Noh, J. Dimasaka, Kishor S. Jaiswal, Kate E. Allstadt, Davis T. Engler

Update on the Center for Engineering Strong-Motion Data (CESMD)

he Center for Engineering Strong-Motion Data (CESMD), an internationally utilized joint center of the U.S. Geological Survey (USGS) and the California Geological Survey (CGS), provides a unified access point for earthquake strong-motion records and station metadata from the CGS California Strong-Motion Instrumentation Program (CSMIP), the USGS National Strong-Motion Project (NSMP), the USGS Advanc
Authors
L. Hagos, H. Haddadi, Lisa Sue Schleicher, Jamison Haase Steidl, Lind Gee, M. Dhar

A novel origin for PGE reefs: A case study of the J-M Reef

The origin of meter scale stratiform layers of disseminated sulfides in enriched platinum group element (PGE) tenors and grades, called reef-type deposits, are the world’s most significant source of PGEs. Their origin in layered mafic intrusions remains debated, but in general, most researchers favor an orthomagmatic origin for reef-type deposits and agree that their formation requires the equilib
Authors
Michael Jenkins, James E. Mungall, Michael L. Zientek, Gelu Costin, Zhuo-sen Yao

What did they just say? Building a Rosetta stone for geoscience and machine learning

Modern advancements in science and engineering are built upon multidisciplinary projects that bring experts together from different fields. Within their respective disciplines, researchers rely on precise terminology for specific ideas, principles, methods, and theories. Hence, the potential for miscommunication is substantial, especially when common words have been adopted by one (or both) group(
Authors
Stanley Paul Mordensky, John Lipor, Erick R. Burns, Cary Ruth Lindsey

Scaling-up deep learning predictions of hydrography from IfSAR data in Alaska

The United States National Hydrography Dataset (NHD) is a database of vector features representing the surface water features for the country. The NHD was originally compiled from hydrographic content on U.S. Geological Survey topographic maps but is being updated with higher quality feature representations through flow-routing techniques that derive hydrography from high-resolution elevation data
Authors
Larry Stanislawski, Ethan J. Shavers, Alexander Duffy, Philip T. Thiem, Nattapon Jaroenchai, Shaowen Wang, Zhe Jiang, Barry J. Kronenfeld, Barbara P. Buttenfield