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Articles 91 - 93 of 93
Full-Text Articles in Geophysics and Seismology
Erratum: New Estimates Of The Magnitude Of The Sea-Level Jump During The 8.2 Ka Event, (Geology (2022), 50(1), (86–90), (10.1130/G49296.1)), Jonathan Obrist-Farner, Mark Brenner, Jeffery R. Stone, Marta Wojewódka-Przybył, Thorsten Bauersachs, Andreas Eckert, Marek Locmelis, Jason H. Curtis, Susan R.H. Zimmerman, Alex Correa-Metrio, Lorenz Schwark, Edward Duarte, Antje Schwalb, Etienne Niewerth, Paula Gabriela Echeverría-Galindo, Liseth Pérez
Erratum: New Estimates Of The Magnitude Of The Sea-Level Jump During The 8.2 Ka Event, (Geology (2022), 50(1), (86–90), (10.1130/G49296.1)), Jonathan Obrist-Farner, Mark Brenner, Jeffery R. Stone, Marta Wojewódka-Przybył, Thorsten Bauersachs, Andreas Eckert, Marek Locmelis, Jason H. Curtis, Susan R.H. Zimmerman, Alex Correa-Metrio, Lorenz Schwark, Edward Duarte, Antje Schwalb, Etienne Niewerth, Paula Gabriela Echeverría-Galindo, Liseth Pérez
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
No abstract provided.
Comprehensive Analysis Of Seismic Signals From Pacaya Volcano Using Deep Learning Event Detection, Jessica L. Devlieg
Comprehensive Analysis Of Seismic Signals From Pacaya Volcano Using Deep Learning Event Detection, Jessica L. Devlieg
Dissertations, Master's Theses and Master's Reports
Pacaya volcano located 30 km SW of Guatemala City, Guatemala, has been erupting intermittently since 1961. Monitoring of seismicity is crucial to understanding current activity levels within Pacaya. Traditional methods of picking these small earthquakes in this noisy environment are imprecise. Pacaya produces many small events that can easily blend in with the background noise. A possible solution for this problem is a machine learning program to pick first arrivals for these earthquakes. We tested a deep learning algorithm (Mousavi et al., 2020) for fast and reliable seismic signal detection within a volcanic system. Data from multiple deployments were used, …
Evaluating The Sensitivity Of Crustal Deformation To Bedrock Hydrology In A Mountain Watershed, Brett J. Oliver
Evaluating The Sensitivity Of Crustal Deformation To Bedrock Hydrology In A Mountain Watershed, Brett J. Oliver
Graduate Student Theses, Dissertations, & Professional Papers
We evaluate the sensitivity of Earth's elastic deformation to groundwater hydraulic diffusivity using coupled groundwater and elastic deformation models. Seasonal changes in terrestrial water storage cause deformation to the Earth’s crust and deeper interior that is within the observational capacity of GPS instruments. We couple finite difference groundwater simulations with geodetic forward models of crustal displacement to investigate the ability of geodetic deformation to constrain bedrock hydrologic properties. We use MODFLOW-2005 to simulate seasonal changes in groundwater flow and storage, and then use the LoadDef elastic deformation model to forward model surface displacement caused by the change in terrestrial water …