Conference Papers
Science Quality and Integrity
The USGS provides unbiased, objective, and impartial scientific information upon which our audiences, including resource managers, planners, and other entities, rely.
The USGS provides unbiased, objective, and impartial scientific information upon which our audiences, including resource managers, planners, and other entities, rely.
Browse almost 5,000 conference papers authored by our scientists and refine search by topic, location, year, and advanced search.
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Multi-period response spectra Multi-period response spectra
Multi-period response spectra (MPRS) are incorporated in the development of seismic design ground motions in the 2020 edition of the NEHRP Recommended Seismic Provisions for New Buildings and Other Structures (2020 NEHRP Provisions) and are approved for adoption in the American Society of Civil Engineers (ASCE) Standard, Minimum Design Loads and Associated Criteria for Buildings and...
Authors
Sanaz Rezaeian, Nico Luco, C. A. Kircher
Near real-time updating of pager loss estimates Near real-time updating of pager loss estimates
Initial alerts by PAGER (Prompt Assessment of Global Earthquakes for Response) within minutes following an earthquake include several uncertainties, mainly due to potential inaccuracies in location, depth, fault delineation, and shaking estimates. We enhance an updating framework by incorporating early reports of fatalities within the first 24 hours, or so, of an earthquake to update...
Authors
Davis Engler, Kishor S. Jaiswal, Hae Young Noh, David J. Wald
Stop 3 – The Petersburg “Granite” redefined: Recognition and implications of Silurian to Devonian rocks in central-eastern Virginia Stop 3 – The Petersburg “Granite” redefined: Recognition and implications of Silurian to Devonian rocks in central-eastern Virginia
Introduction Although the Petersburg Granite had long been in practical use as a building stone since the 1830s (Watson, 1906; 1907; 1910; Darton, 1911; Steidtmann, 1945), it was first formally defined as a geologic unit by Anna Jonas on the 1928 geologic map of Virginia. Anna Jonas defined this unit as a Precambrian coarse-grained porphyritic biotite granite that was intruded by finer...
Authors
Mark W. Carter, Ryan J. McAleer, Marcie Occhi, Christopher S. Holm-Denoma, Jorge A. Vazquez, Brent E. Owens
Numerical modelling of mine pollution to inform remediation decision-making in watersheds Numerical modelling of mine pollution to inform remediation decision-making in watersheds
Prioritisation of mine pollution sources for remediation is a key challenge facing environmental managers. This paper presents a numerical modelling methodology to evaluate potential improvements in stream water quality from remediation of important mine pollution sources. High spatial resolution synoptic sampling data from a Welsh watershed were used to calibrate the OTIS solute...
Authors
Patrick Byrne, Patrizia Onnis, Robert L. Runkel, Ilaria Frau, Sarah F. L. Lynch, Aaron M. L. Brown, Iain Robertson, Paul Edwards
Risk-informed levee erosion countermeasure site selection and design in the Sacramento area part 2: Probabilistic numerical simulation of bank erosion Risk-informed levee erosion countermeasure site selection and design in the Sacramento area part 2: Probabilistic numerical simulation of bank erosion
USACE partnered with the United States Department of Agriculture, Agricultural Research Service, United States Geological Survey, and Texas A&M University to evaluate the erodibility of the river banks and levees to inform probabilistic numerical simulations using the Bank Stability and Toe Erosion Model (BSTEM). This paper, the second of two parts, addresses processing the collected...
Authors
Todd M. Rivas, Jonathan AuBuchon, Anna Shidlovskaya, Eddy J. Langendoen, Paul A. Work, Daniel N. Livsey, Anna Timchenko, Kellie Jemes, Jean-Louis Briaud
Risk-informed levee erosion countermeasure site selection and design in the Sacramento area part 1: Soil sampling, testing, and data processing Risk-informed levee erosion countermeasure site selection and design in the Sacramento area part 1: Soil sampling, testing, and data processing
USACE partnered with the United States Department of Agriculture, Agricultural Research Service, United States Geological Survey, and Texas A&M University to evaluate the erodibility of the river banks and levees to inform probabilistic numerical simulations using the Bank Stability and Toe Erosion Model (BSTEM). This paper discusses the measurement of the intrinsic erosion and...
Authors
Todd M. Rivas, Jonathan AuBuchon, Anna Shidlovskaya, Eddy J. Langendoen, Paul A. Work, Daniel N. Livsey, Anna Timchenko, Jean-Louis Briaud
Monitoring multi-decadal variations of urban heat island intensity Monitoring multi-decadal variations of urban heat island intensity
Urban development and associated land cover transitions alter the thermal and physical properties of the land surface, resulting the temperature in urban area higher than in rural area or urban heat island (UHI). Remote sensing and land cover data is usually used to assess UHI intensity and temporal change trends. In this study, we implemented a prototype approach to characterize the UHI...
Authors
George Z. Xian, Hua Shi, Kevin Gallo
SUAS and machine learning integration in waterfowl population surveys SUAS and machine learning integration in waterfowl population surveys
The rapid technological development of small Unmanned Aircraft Systems (sUAS) has led to an increase in capabilities of aerial image collection and analysis for monitoring a variety of wildlife species including waterfowl. Biologists mainly rely on conducting ocular surveys from fixed-wing aircraft or helicopters to estimate waterfowl abundance. sUAS provide an alternative that is safer...
Authors
Z. Tang, Y. Zhang, Y. Q. Wang, Y. Shang, R. Viegut, Elisabeth B. Webb, Andy Raedeke, J. Sartwell
Digital Twin Earth - Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators Digital Twin Earth - Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators
Developing fast and accurate surrogates for physics-based coastal and ocean mod- els is an urgent need due to the coastal flood risk under accelerating sea level rise, and the computational expense of deterministic numerical models. For this purpose, we develop the first digital twin of Earth coastlines with new physics-informed machine learning techniques extending the state-of-art...
Authors
P. Jiang, N. Meinert, H. Jordao, C. Weisser, S. Holgate, A. Lavin, B. Lutjens, D. Newman, H. Wainright, C. Walker, Patrick L. Barnard
Physics-guided machine learning from simulation data: An application in modeling lake and river systems Physics-guided machine learning from simulation data: An application in modeling lake and river systems
This paper proposes a new physics-guided machine learning approach that incorporates the scientific knowledge in physics-based models into machine learning models. Physics-based models are widely used to study dynamical systems in a variety of scientific and engineering problems. Although they are built based on general physical laws that govern the relations from input to output...
Authors
Xiaowei Jia, Yiqun Xie, Sheng Li, Shengyu Chen, Jacob Aaron Zwart, Jeffrey Michael Sadler, Alison P. Appling, Samantha K. Oliver, Jordan Read
Data-driven prospectivity modelling of sediment-hosted mineral systems Data-driven prospectivity modelling of sediment-hosted mineral systems
Mississippi Valley-type (MVT) and clastic-dominated (CD) deposits are important sources for Zn, Pb, Ag, and Cd as well as the critical elements Ga, Ge, In, and Sb. However, mapping the drivers, sources, pathways, and traps of MVT and CD deposits within the much larger and mostly unmineralized sedimentary basins remain some of the least understood aspects of these mineral systems. Herein...
Authors
Christopher J.M. Lawley, Anne E. McCafferty, Garth E. Graham, Michael G. Gadd, David L. Huston, Karen D. Kelley, Karol Czarnota, Suzanne Paradis, Jan M. Peter, Nathan Hayward, Mike Barlow, Poul Emsbo, Joshua A. Coyan, Carma A. San Juan
Exploring basin-scale relations and unsupervised classification to quantify and automate the definition of assessment units in USGS continuous oil and gas resource assessments Exploring basin-scale relations and unsupervised classification to quantify and automate the definition of assessment units in USGS continuous oil and gas resource assessments
The U.S. Geological Survey (USGS) assesses potential for undiscovered, technically recoverable oil and gas resources in priority geologic provinces and quantifies resource volume estimates within subdivisions called assessment units (AUs). AU boundaries are defined by USGS geologists using quantitative and qualitative geologic information. Variables contained in IHS Markit’s well and...
Authors
Chilisa Marie Shorten, Scott A. Kinney, Katherine J. Whidden