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William Chen
Project Title: Defining the Source Fault of the 1886 Summerville, South Carolina Earthquake
This project explores the moment magnitude ~7 1886 Summerville, South Carolina earthquake. Partially due to a lack of faulting on the surface, the source and nature of this earthquake has previously been difficult to ascertain. Therefore, for the purpose of elucidating the fault structure of the region, a recent deployment of seismic stations in the region has been recording continuous data since early 2021. Within this data, as well as within data from nearby permanent seismic stations, I will be identifying seismic events using both matched-filter techniques and deep-learning methods, allowing for detection of a larger number of earthquakes than manual picking alone. I will then be relocating the identified modern seismic events allowing for better observation of the fault structures of the area. Finally, these results will be compared to results of previous deployments and the source fault of the original 1886 Summerville earthquake will be more precisely identified.
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Alaura Custard
Project Title: Characterizing Basin Amplification in the Portland, OR, Metro Area
The amplification of earthquake shaking in sedimentary basins is a major cause of seismic hazard. Often, the ground motions within a basin can be increased by a factor of two or more. While sedimentary basins beneath cities like Los Angeles and Seattle have been studied to characterize basin amplifications, the Tualatin Basin near Portland has not been very well studied. Recently it was discovered that the basin is much deeper than originally thought. The proximity of the Tualatin basin to the Cascadia subduction zone and other large faults has raised concerns about the amplification possible in this basin. Using ambient seismic data collected from broadband seismometers, this project will apply common seismic hazard analysis methods to better characterize the Tualatin basin’s amplification of seismic waves.
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Suzie Duran
Project Title: Multi-sensor investigations of acoustic signals recorded in Alaska from the January 2022 Hunga, Tonga eruption
My research for the Summer is taking place at the Geophysical Institute (GI) at the University of Alaska, Fairbanks. I will be conducting research on seismo-acoustic wave propagations initiated by the January 15th, 2022 Hunga, Tonga eruption whose atmospheric acoustic waves were captured by Alaska’s dense array of multi-sensor stations. The powerful surtseyan eruption of this underwater volcano was so explosive it caused an audible atmospheric wave greater than 20Hz, generated tsunamis on the west coast of North America, and caused seismic and acoustic waves to travel around the world multiple times. In order to analyze the geophysical data from the Tonga eruption, open-source Python tools, such as ObsPy and PyGMT, code collaboration via GitHub, and data from IRIS’ Data Management Center (DMC) play a critical role in collecting essential information. The main source of the data is recorded via the U.S. Earth Scope Transportable Array (US-TA) which is part of a dense network of seismic/infrasound stations (~400 stations with various networks) across Alaska, eastern Canada, and the lower 48. In Alaska, the US-TA was originally comprised of 280 stations, spaced 85km apart, of which only 72 are now operating under Alaska’s Earthquake Center (AEC) which is part of the GI. Using the data from Alaska’s array of multi-sensor stations will help determine which sensors recorded acoustic waves from the Hunga eruption. The data acquired from the US-TA helps to provide geoscientists with information about the interior structure of the Earth beneath North America and provides seismic and infrasound wave data lower than 20 Hz (inaudible to humans) which propagate through the atmosphere.
I will be analyzing the effectiveness of using low-budget seismometers to determine earthquake energy and duration. There is currently a network of these seismometers, called raspberry shakes, being deployed across the globe collecting data. I will compare this data to data collected through larger seismic networks such as IRIS by creating plots of the raspberry shake data and conducting statistical analysis. This analysis will be done using python, and earthquake energy will be calculated with the program RTergPy which was developed at Georgia Tech. If the low-budget instruments are found to be useful in collecting the desired information, they have the potential to be deployed in more places than their more expensive counterparts. This wider deployment would be useful in quickly detecting earthquakes at midocean ridges that may cause large tsunamis and give an early warning system for these events.
My project will examine Rayleigh wave propagation across Alaska, with the end goal of creating a number of tomographic maps of the state. This region is tectonically interesting because it contains certain features that are not fully understood, such as the role of the Yakutat Terrain in influencing subduction and the processes responsible for forming the Wrangell Volcanic Field. To do this, the travel times of Rayleigh waves from various earthquakes to Canadian and Alaskan seismic stations will be used to generate maps and eventually image variations in wave attenuation (amplitude decay) and velocity at depths between 30-200 km. These wave characteristics are linked to subsurface features such as temperature, composition, and the presence of water or partial melt; as such, they may help relate the interesting surface features to the underlying crust and upper mantle. Data primarily from the EarthScope Transportable Array taken between 2015 and 2021 will be used, and analyzed in Matlab.
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Chris Justiniano
Project Title: Waveform Correlation and Machine Learning Applied to Induced Earthquakes
This summer research relies on studying induced earthquakes common from Texas's local basins as a result of wastewater injection since 2008, with the additional purpose of expanding Texas’s earthquake catalog from local and regional data to seismic events of lower magnitude related to these injection methods. I'll study specifically the North area of the Fort-Worth Basin, since this is the region that SMU campus is currently doing part of their extensive research, along with data collected by their local seismic stations. I will be in charge of identifying phase changes, locate earthquakes, and process seismic waveform data from North Texas catalog through coding and data analysis, with main emphasis in Python. These clusters are based on InSAR, infrasound, and other seismologic tools. Machine learning will be applied as a tool to better understand the distribution of earthquakes and how much affect local communities nearby Dallas. The main outcome of the research is to have an extensive earthquake catalog of Texas with more seismic events of lower magnitude.
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Eve Paulson
Project Title: Shear wave splitting at western Alaska-Aleutian volcanoes
This summer I will be working on using a technique called shear wave splitting to look at flow directions in the mantle beneath the Aleutian arc volcanoes in Alaska. The volcanoes in this area generally get smaller moving east to west and also tend to produce different lavas. In the eastern part of the arc, the volcanoes produce lavas that contain evidence of recycled surrounding material like sediments, while the volcanoes in the western part of the arc show very little recycling. Right now, the reason for the differences in size and lava composition isn’t well known. I will be looking for correlations between mantle flow and the volcanic trends in the Aleutian arc. From there we can investigate whether trends in the volcanoes at the surface can tell us anything about the structure of the subsurface. It's possible that these surface volcanoes are related to the flow and thermal structure of the mantle, which can also give us insight into how magma, water, and other volatile gasses move in the subsurface. These methods could be applied to other locations where we have unexplained differences in volcanoes that are part of the same system to further develop our understanding of the relationship between surface volcanoes and mantle wedge dynamics.
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Andrew Sparks
Project Title: Hunting Dust Devils in the Desert with Infrasound Sensors
The goal of this project is to successfully detect dust devil signals within infrasound data gathered in the Mojave Desert in Nevada. Dust devils, or dust-loaded convective vortices, feature a low pressure center, which reads on infrasound sensors as a characteristic heart-beat shaped dip and peak signal. Leveraging the specific signal that dust devils create, we plan to use waveform cross correlation to try and detect them automatically, trialing the procedure first on generated synthetic data to appraise the accuracy and limitations of the algorithm in actually detecting dust devils. The larger goal of this project is to better understand the factors controlling dust devil formation and size, with the purpose of using that information to better plan Martian missions to take advantage of the solar panel clearing that dust devils provide.
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Anna Teurman
Project Title: Mapping the mantle transition zone with convolutional neural networks
There is a lot we still don’t know about the structure and dynamics of the Earth. Using machine learning and convolutional neural networks (CNNs), both of which train a computer to recognize patterns, I will be using data from earthquakes to investigate the transition zone of the mantle. As we travel down through the mantle, pressure and temperature increase which causes the materials which make up the mantle to change phase. Notable areas where the materials change can be seen around 410km, 660km, and sometimes 520km. Earthquakes travel outward as waves, these waves also travel through the Earth with their speed changing depending on the material through which they travel. Specifically, I will be looking at waves that have bounced off the underside of the transition zone. These waves are called precursors as they arrive before waves that bounce off the surface of the Earth. We are using machine learning and CNNs as they expedite the identification of these precursor signals. The information we gather will be used to better understand the structure and dynamics of the mantle's transition zone.
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Cherilyn Toro
Project Title: Mantle wedge dynamics in the Alaska-Aleutians subduction zone
This project will examine the patterns of mantle wedge dynamics of the Alaska-Aleutians Subduction Zone using the shear wave splitting technique of local S seismic phases to look at the flow directions in the mantle, and with these results we can infer the flow change along the subduction zone and the variable dynamics operating within the mantle wedge. The importance of this project is related to a better understanding of the aspects of the controlling mantle wedge dynamics in this subduction zone, and a better assess to the risks associted to it.
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Jenelle_Cockerham
Project Title: Exploring how groundwater and soil chemistry on a landscape affect streams
In this project we are studying the activity of water in Crusted Butte, CO. The objective is to study the hydrologic events, understand and notice the changes in groundwater flow, stream discharge, bedrock weathering, and nutrient cycling throughout the year drive changes in meta(loid) concentrations in groundwater. The last goal is to understand physical and biogeochemical processes combine to shape meta(loid) fate and transport processes in streams.