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.
Filter Total Items: 5619
Linear deconvolution applied to ASTER imagery of terrestrial dune analog sites Linear deconvolution applied to ASTER imagery of terrestrial dune analog sites
Advanced Spaceborne Thermal Emission and Reflec-tion (ASTER) radiometer onboard NASA’s Terra satellite has nearly complete global coverage in the 8 – 14 µm thermal infrared (TIR) atmospheric window and is the highest resolution sensor providing TIR emissivity data at 90-m spatial resolution and five multispectral bands. ASTER imagery enables mapping of spatial variations in the...
Authors
Donald M. Hooper, Bernard E. Hubbard
2021 Computational Infrastructure for Geodynamics Developers Workshop 2021 Computational Infrastructure for Geodynamics Developers Workshop
The CIG Developers Workshop resulted in a number of recommendations that we think will help expand the CIG developer community, make software more accessible to new users, and increase developer productivity through use of common infrastructure and best practices for software development. This includes building a broad user base with sufficient support through documentation, tutorials...
Authors
Brad T. Aagaard, Jed Brown, Catherin Cooper, Rene Gassmoeller, Lorraine Hwang, Marc Spiegelman
National-scale reservoir thermal energy storage pre-assessment for the United States National-scale reservoir thermal energy storage pre-assessment for the United States
The U.S. Geological Survey is performing a pre-assessment of the cooling potential for reservoir thermal energy storage (RTES) in five generalized geologic regions (Basin and Range, Coastal Plains, Illinois Basin, Michigan Basin, Pacific Northwest) across the United States. Reservoir models are developed for the metropolitan areas of eight cities (Albuquerque, New Mexico; Charleston...
Authors
Jeffrey D. Pepin, Erick R. Burns, Jesse E. Dickinson, Leslie L. Duncan, Eve L. Kuniansky, Howard W. Reeves
Evolution of fluid transmissivity and strength recovery of shear fractures under hydrothermal conditions Evolution of fluid transmissivity and strength recovery of shear fractures under hydrothermal conditions
Geothermal systems rely on the presence of long-lived and high-volume, permeable fracture systems. The creation, reactivation, and sustainability of these systems depend on complex coupling among thermal, hydraulic, mechanical, and chemical (THMC) processes occurring in geothermal reservoirs. In part due to a paucity of experimental data, the evolution of fractures at geothermal...
Authors
Tamara Nicole Jeppson, David A. Lockner, Brian D. Kilgore, Nicholas M. Beeler, Joshua M. Taron
Subsurface characterization and machine learning predictions at Brady Hot Springs Subsurface characterization and machine learning predictions at Brady Hot Springs
Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulations have been conducted in TETRAD-G and CMG STARS to explore different injection and production fluid flow...
Authors
Koenraad F. Beckers, Dmitry Duplyakin, Michael J. Martin, Henry E. Johnston, Drew L. Siler
Learning augmented methods for matching: Improving invasive species management and urban mobility Learning augmented methods for matching: Improving invasive species management and urban mobility
With the success of machine learning, integrating learned models into real-world systems has become a critical chal- lenge. Naively applying predictions to combinatorial opti- mization problems can incur high costs, which has motivated researchers to consider learning augmented algorithms that can make use of faulty or incomplete predictions. Inspired by two matching problems in...
Authors
Johan Bjorck, Qinru Shi, Carrie Brown-Lima, Jennifer Dean, Angela K. Fuller, Carla Gomes
S2HM must be real-time or not? S2HM must be real-time or not?
Seismic structural health monitoring (S2HM) has advanced significantly in the last three decades. However, currently there is no consensus on the need for real-time processing of data acquired during an earthquake. Numerous applications exist whereby S2HM-equipped systems record valuable seismic response data. A delayed use of the seismic data prohibits timely discovery of hidden damages...
Authors
Mehmet Celebi, Maria Limongelli
Embracing the Future: Promoting adaptation and resilience to invasive species and climate change Embracing the Future: Promoting adaptation and resilience to invasive species and climate change
No abstract available.
Authors
Bianca Lopez, Carrie Brown-Lima, Justin Dalaba, Annette Evans, Meghan Graham MacLean, Toni Lyn Morelli
A Year-long Hydroacoustic Survey of the Mariana Islands Region A Year-long Hydroacoustic Survey of the Mariana Islands Region
The Mariana Islands region hosts interesting geological features as well as abundant biodiversity. The subduction zone and back-arc spreading center have led to active volcanism that can have impacts on local islanders, aircraft flying in the region, and military activities. We deployed a small aperture hydrophone array from June 2017 to June 2018 in the Marianas back-arc to better...
Authors
Gabrielle Tepp, Robert P. Dziak, Matthew M. Haney, Lauren Roche, Haru Matsumoto
Model structural uncertainty quantification and hydrogeophysical data integration using airborne electromagnetic data Model structural uncertainty quantification and hydrogeophysical data integration using airborne electromagnetic data
Airborne electromagnetic (AEM) dataare usedto estimate large-scale model structural geometry, i.e. the spatial distribution of different lithological units based on assumed or estimated resistivity-lithology relationships, and the uncertainty in those structures given imperfect measurements. Geophysically derived estimates of model structural uncertainty are then combined with hydrologic
Authors
Burke J. Minsley, Nikolaj K Christensen, Steen Christensen, Yusen Ley-Cooper
Partial differential equation driven dynamic graph networks for predicting stream water temperature Partial differential equation driven dynamic graph networks for predicting stream water temperature
This paper presents a physics-guided machine learning approach that incorporates partial differential equations (PDEs) in a graph neural network model to improve the prediction of water temperature in river networks. The standard graph neural network model often uses pre-defined edge weights based on distance or similarity measures. Such static graph structure can be limited in capturing...
Authors
Tianshu Bao, X. Jia, Jacob Aaron Zwart, Jeffrey Michael Sadler, Alison P. Appling, Samantha K. Oliver, Taylor T. Johnson
Process-based models and studies of coastal change to inform habitat restoration and climate change adaptation Process-based models and studies of coastal change to inform habitat restoration and climate change adaptation
Puget Sound salmon and estuary recovery strategies identify tens of thousands of acres of floodplain and estuary habitat restoration needed to re-establish ecosystem functions lost or degraded from western land use (Simenstad et al., 2011); the extent for nearshore habitat remains uncertain. Sediment is critical for shaping the structure and functions of these ecosystems and the success...
Authors
Eric E. Grossman