Projects for Summer 2023

Potential Projects

Ice Penetrating Radar: Science and Engineering to Explore Ice Sheets and Icy Moons

SESUR, SURGE
Category(s): Climate Change, Dynamic Earth, Planetary Science
Department: Geophysics
Mentor: Prof Dusty Schroeder

The Stanford Radio Glaciology research group focuses on the subglacial and englacial conditions of rapidly changing ice sheets and the use of ice penetrating radar to study them and their potential contribution to the rate of sea level rise. In general, we work on the fundamental problem of observing, understanding, and predicting the interaction of ice and water in Earth and planetary systems. Radio echo sounding is a uniquely powerful geophysical technique for studying the interior of ice sheets, glaciers, and icy planetary bodies. It can provide broad coverage and deep penetration as well as interpretable ice thickness, basal topography, and englacial radio stratigraphy. Our group develops techniques that model and exploit information in the along-track radar echo character to detect and characterize subglacial water, englacial layers, bedforms, and grounding zones. In addition to their utility as tools for observing the natural world, our group is interested in radio geophysical instruments as objects of study themselves. We actively collaborate on the development of flexible airborne and ground-based ice penetrating radar for geophysical glaciology, which allow radar parameters, surveys, and platforms to be finely tuned for specific targets, areas, or processes. We also collaborate on the development of satellite-borne radars, for which power, mass, and data are so limited that they require truly optimized designs. Student projects are available in support of both ice penetrating radar instrument development and data analysis.

Skills/Interest/Background: Computer Programming, Engineering, Physics, Scientific Programming

The Arctic Ocean: A Tale of Three Systems

SESUR
Category(s): Climate Change, Dynamic Earth, Ocean
Department: Earth System Science
Mentor: Prof Kevin Arrigo, Mentor: Matt Mills, Mentor: Gert van Dijken

Detailed observations of microalgal blooms in the Chukchi Sea have been largely made at a time of year when most of the Chukchi shelf is already in open water. As such, the relative rates of daily net primary production (NPP) by sea ice microalgae, phytoplankton living beneath the ice, and phytoplankton in open water are not well known. Additionally, the fate of the organic matter associated with these three NPP sources is poorly known. Hence, there is a strong need for comprehensive measurements beginning in late spring that capture all three blooms, with particular emphasis on particle export events.

Ideally, our field campaign in the summer of 2023 will allow us to capture the transitions between the sea ice algal bloom, under-ice blooms (UIBs), and blooms in the open ocean. Our primary objectives are to 1) Compare the biomass accumulation and daily rates of NPP for microalgae associated with sea ice, UIBs, and open water blooms, 2) Assess the vertical sinking rates of individual particles associated with microalgal blooms associated with sea ice, UIBs, and open water and the factors controlling those rates, and 3) Determine the vertical export flux of organic C fixed by sea ice microalgae, UIBs, and open water phytoplankton.

The student would be expected to participate in a 45-day research cruise to the Chukchi Sea from early June to late July 2023. The student's duties would be to help collect and analyze samples on board ship and provide general assistance to the research team.

Skills/Interest/Background: Biology

Sketch to 3D for real-time design feedback

SURGE
Category(s): Climate Change, Energy, Human Dimensions and Sustainability, Planetary Science
Department: Civil & Environmental Engineering
Mentor: Prof Martin Fischer, Mentor: ALBERTO TONO

The Stanford Center for Integrated Facility and Engineering (CIFE) is researching how to answer the ever-growing construction demand, properly. This project targets the latency between schematic and development design phases in today’s Architecture, Engineering, and Construction (AEC) workflows. This high latency problem is caused by technology bottlenecks and insufficient information to make real-time informed decisions. To solve this issue, we are exploring state-of-the-art research in artificial intelligence (AI) for Virtual Design and Construction (VDC) and Building Information Modeling (BIM). Indeed, from simple inputs (sketch, audio, text, image), Generative AI produces actionable information related to geometry, semantics, construction costs, energy consumption, structure, wind, construction schedule, and cost. This summer project will focus mainly on modalities such as sketches and text. Furthermore, we will improve our open-source tool Vitruvio, integrating it with Omniverse (NVIDIA) and other design tools. This project will focus on how AI can augment human capabilities in designing more collaboratively, environmentally sound, and sustainable buildings.

Skills/Interest/Background: Computer Programming, Engineering, Machine Learning, Mathematics, Scientific Programming, Statistics

American Public Opinion on Climate Change

SURGE
Category(s): Human Dimensions and Sustainability
Mentor: Prof Jon Krosnick

For more than a decade, my team has been studying what the American public thinks about climate change. And in numerous surveys, we have found that the vast majority of Americans are on the "green" side of the issue. But in recent surveys, we have conducted numerous experiments exploring how survey question wording influences responses. This is an opportunity to study the impact of question wording generally in surveys (can survey results be believed? Or are they so fragile and easily manipulated by question wording that they should not be trusted?) and the robustness of Americans' opinions on the issue. We will conduct statistical analyses of the data collected in these experiments, and write up a paper for publication.

The undergraduate will build the databases for analysis using many survey datasets, and then the student will conduct statistical analyses of the data using Stata or R and will draft a manuscript.

The student will benefit in the following ways: (1) gaining understanding of the structure and nature of survey research, (2) gaining understanding of procedures to design and conduct objective data collection, (3) gaining understanding of conducting elementary statistical analysis of quantitative data, (4) gaining understanding of how to write up research findings in ways suitable for publication in academic journals, and (5) gaining understanding of how to design and conduct experiments embedded in surveys to document the causal impact of news stories on people’s opinions. The student will work as part of a large team of post-docs, graduate students, and undergraduates working with Professor Krosnick and will participate in regular meetings with the team, which will provide exposure to scientific careers and offer resources on which to draw when learning how to do work. And the student will meet weekly with Professor Krosnick to review and plan research activities.

It would be desirable for the student to have experience with statistics and data base management, but these skills are not necessary. We welcome all students who are interested in understanding how to use scientific methods to document public opinion about climate change and to learn about the science of survey research.

Skills/Interest/Background: Statistics

Sustainable Nutrient Cycling in California Cropland: Understanding Cover Crop Residue Mineralization to Inform Groundwater Pollution Policy

SURG
Category(s): Climate Change, Food and Agriculture
Department: Earth System Science
Mentor: Prof Scott Fendorf, Mentor: Anna Gomes

A student for this project has been found.

Amidst ongoing concerns around water quality, drought conditions, and the urgency to decarbonize food production, vegetable crop farmers need soil management strategies that can both ensure yields and soil health while reducing global net greenhouse gas (GHG) emissions and nitrogen pollution. Cover crops, which can be grown during the time period between cash crops, are one such practice and are being considered for inclusion in current policy.

Known as the ‘salad bowl of the world’, California’s Salinas Valley is a high input, high intensity cropping system which has led to nitrate groundwater pollution poisoning our communities and ecosystems. A recent policy has emerged in this region, Ag Order 4.0, which is requiring farmers to monitor their fertilizer practices and to gradually reduce their soil nitrogen surplus. Cover crops with a C:N (carbon to nitrogen) ratio of at least 20:1 are incentivized within the policy, as they have been shown to scavenge surplus nitrogen from the soil. However, there exists a knowledge gap as to the nitrogen dynamics of growing and harvesting cover crops with lower C:N ratios due to their unknown biomass mineralization. Once cover crops are grown and then incorporated into the soil, we need to understand how they are decomposed by soil organisms and how much nitrogen is ‘released’ or ‘mineralized’.
This project consists of measuring mineralized carbon and nitrogen over an 84 day soil laboratory incubation of different cover crop biomass types and rates of residual soil nitrogen (representing conventional crop production systems).

Experiment Incubation Tasks include:
- Preparation: characterizing soil and cover crop biomass with laboratory analysis methods (pH, carbon, nitrogen, moisture, etc.), sieving soil, and filling tubes
- Measurements: taking soil CO2 measurements, destructive soil sampling, mineral nitrogen extractions
- Results: preparing and running samples on laboratory machines, processing and understanding the data, and writing code in R to visualize and analyze our findings

No previous laboratory experience or R knowledge is required for your participation in this project; only enthusiasm, a willingness to learn, and a curiosity for the wonderful world of soil biogeochemistry and agricultural crop production are encouraged.

Skills/Interest/Background: Biology, Chemistry, Computer Programming, Lab Work, Statistics

Plants in a changing world: Computer modeling of plant water use and carbon uptake

SESUR, SURGE
Category(s): Climate Change, Dynamic Earth, Freshwater
Department: Earth System Science
Mentor: Prof Alexandra Konings, Mentor: Trent Robinett

Approximately one third of the carbon dioxide emitted by humans is taken out of the atmosphere by trees and plants. This makes vegetation a vital resource for offsetting human greenhouse gas emissions. However, the ability for a plant to sequester carbon is not constant; it depends on the environmental conditions in which the plant exists, such as water availability, temperature, and humidity. Therefore, understanding whether vegetation will continue to partially offset human emissions in a hotter and drier world requires accurately predicting plant water use and carbon uptake under varying conditions.

Current computer models focus on first predicting the rate at which plants use water, known as stomatal conductance, since this largely determines a plant’s rate of photosynthesis. Despite this importance, such stomatal conductance models are inaccurate. We have recently developed a new model that aims to address some of the limitations of previous models with the hope of more accurately predicting the role of plants in the carbon and water cycles.

We are looking for a motivated student to spearhead a project aimed at better understanding the implications of this newly developed model. The project looks to first understand if the new model matches observations better than previous models. Additional questions that can be investigated include: what features in this new model are most important for correctly predicting plant water use and photosynthesis; why does one model feature matter more than another model feature; and many more! The ideal candidate will have experience manipulating data using a programming language such as Python, R, or Matlab. Previous experience in biological modeling is not required. The student will gain experience working with biological models and will gain skills applicable to data analysis.

Skills/Interest/Background: Biology, Scientific Programming

Advancing the Use of Marine Environmental DNA as a Tool for Marine Biodiversity Monitoring

SESUR, SURGE
Category(s): Human Dimensions and Sustainability, Ocean
Department: Civil & Environmental Engineering, Department: Emmett Interdisciplinary Program in Environment & Resources
Mentor: Prof Alexandria Boehm, Mentor: Meghan Shea

Scientists and conservationists are increasingly using environmental DNA (eDNA; the bits of DNA that organisms leave behind in the environment) as a way to measure biodiversity, including in ocean environments. eDNA has the potential to make monitoring marine ecosystems much easier and cheaper, but there are still many big scientific questions about what eDNA samples represent and how best to interpret the data they produce. But advancing the use of eDNA doesn’t just require scientific work; we also need a better understanding of how scientists, policymakers, and the public think about the promises and pitfalls of the technology.

We have several ongoing projects—ranging in approach from natural science to social science—that undergraduate research collaborators could support or lead, including: - comparing eDNA samples collected in the intertidal at Pillar Point, Half Moon Bay, CA with other types of biodiversity data from the site - designing an effective scientific plan and engagement strategy for involving the public in eDNA sample collection (via citizen/community science) - analyzing how articles in the media describe the potential uses of marine eDNA - analyzing interviews conducted with interdisciplinary researchers using eDNA for the first time to better understand their questions and hesitations about the technology.

None of the projects above have any required qualifications, and each of the projects above would help you build different combinations of skills. But overall, you could be an especially good fit if at least one of the qualifications below applies to you: - Excited to learn more about marine environmental DNA - Experience conducting a large literature review - Experience with environmental communication and/or community engagement - Experience analyzing natural science and/or social science data - Experience with R, GIS, or NVivo - Experience with statistical analysis All research collaborators will learn more about marine eDNA, gain specific skills and experiences related to their particular project, and be exposed to other interdisciplinary approaches. If you are interested in marine eDNA, but not any of the particular projects outlined, there may be opportunities to design or contribute to other related projects; please don’t hesitate to reach out.

Skills/Interest/Background: Biology, Computer Programming, Engineering, Field Work, Lab Work, Scientific Programming, Statistics

Life in Extremes: Investigating the Physiology and Genomic Adaptations of Microorganisms in the Deep Sea and Hypersaline Brines

SESUR, SURGE
Category(s): Evolution of Earth, Ocean
Department: Earth System Science
Mentor: Prof Anne Dekas, Mentor: Rebecca Salcedo, Mentor: Dr Alexander Jaffe

The deep sea is the largest habitat on Earth, covering nearly 70% of Earth’s surface. Life in the deep sea poses multiple challenges that must be overcome by organisms that live there, including extreme pressure, limited nutrients, and complete darkness. Some microbes also experience high salinity within sunken, salty lakes on the ocean floor called DHABs (deep, hypersaline, anoxic basins). Understanding how microbial life has adapted to both the deep sea and DHABs allows us to explore the limits of life on our planet while also informing the search for life on other planetary bodies with extreme and hypersaline environments, such as the moons of Jupiter and Saturn.

In this project, we will be studying the micro-organisms (bacteria and archaea) associated with deep-sea ecosystems from the North Pacific and the Gulf of Mexico. A particular microbial group of interest is the Thaumarchaea, an abundant group in the deep sea that perform important ecosystem services like regulating the carbon and nitrogen cycles. We will extract DNA from microbial communities containing Thaumarchaea, perform metagenomic sequencing, and analyze how these organisms (and possibly others) are adapted to their extreme environments with comparative approaches. The project may also entail culturing of Thaumarchaeota that could further reveal their physiology and metabolism.

We are seeking a candidate who is eager to combine multiple approaches from molecular biology, microbiology, and computational biology to study deep-sea extremophiles. The balance of approaches, as well as specific genomic questions, are flexible and can be tailored to the candidate’s personal research interests. Regardless, the candidate will gain hands-on experience with culturing microbes, the preparation and analysis of metagenomic datasets, common bioinformatic tools for analyzing them, and high-performance scientific computing environments. The student will work closely with a graduate student and postdoctoral researcher and should expect a highly collaborative experience that will culminate in a research presentation at the end of the summer.

Experience in DNA extraction, microbial cultivation, and bioinformatics is beneficial, but not necessary - we are happy to train the right candidate. If you’re excited about marine microbiology, astrobiology, or microbial genomics, please consider applying!

Skills/Interest/Background: Biology, Computer Programming, Lab Work, Scientific Programming, Statistics

Sea level rise impacts on regional liquefaction hazard

SURGE
Category(s): Climate Change, Natural Hazards
Department: Civil & Environmental Engineering
Mentor: Prof Jack Baker, Mentor: Emily Mongold

Climate-change driven sea level rise increases shallow coastal groundwater levels, causing more soil to be susceptible to liquefaction. Liquefaction is the phenomenon of ground failure during an earthquake, where saturated soil acts as a liquid and flows or settles. This can cause significant damage to buildings, pipes, and other infrastructure.

The goal of this project is to analyze liquefaction hazard under sea level rise and quantify uncertainty in future hazards and impacts. Research tasks will include data exploration, running analyses, interpreting results, reading relevant literature, and presenting in a group meeting. There may also be an opportunity to participate in meetings with stakeholders. Candidates should be excited about the topic of natural hazards or climate change, be willing to learn, and have some experience coding. Ability to code in Python is preferred, but not required.

Skills/Interest/Background: Computer Programming, Engineering, Statistics

Earth’s history in a grain of sand

SESUR
Category(s): Dynamic Earth, Evolution of Life, Planetary Science
Mentor: Prof Mathieu Lapôtre, Mentor: M. Colin Marvin, Mentor: Carlos A. Alvarez

Sand transported across the surface of the earth by wind, water, and ice is molded differently depending on the forces acting on the grain. Scratches, cracks, and more complex surface textures on sand grains can help us understand a grain’s journey and decipher the history of our planet. However, much is still unknown about how transport distance (e.g., how far downstream in a river) effects the types and abundances of surface textures. Bridging this gap would allow us to determine transport distances of sand grains in ancient rocks, providing critical constraints on the size of earth’s rivers over time.

In this project, our goal is to experimentally test how transport distance affects sand grain surface textures. To do this we will simulate sand moving downstream a river using abrasion mills. Each mill will be filled with water and sand and left to run for a predetermined amount of time. Fresh sand will be created by crushing rock so grains will have pristine crystal shapes. Mills will be set to different speeds so some grains ‘hop’ (bedload) and others are entrained in the flow (suspension). After running each experiment for a known amount of time, we will extract the sand from the mill and image it under an electron microscope and document the textures we see.

The project will involve the student in a variety of tasks throughout the experiments: rock crushing, mineral separation, mill setup, sample preparation, microscope imaging, and data analysis and interpretation. The participant will develop their skills in experimental design and data analysis. Students with lab experimental backgrounds are encouraged to apply. We welcome students from the earth/planetary sciences, atmospheric/ocean sciences, geology, geography, engineering, physics, or similar. Prior experience in geomorphology, sedimentology, or surface processes is not required. We are also open to recruiting STEM students who are beginning to explore the field of earth and environmental sciences.

Skills/Interest/Background: Geology, Lab Work

Will hydrogen-powered aircraft form more climate forcing contrails?

SURGE
Category(s): Built Environment, Climate Change, Energy
Department: Civil & Environmental Engineering
Mentor: Prof Catherine Gorle, Mentor: Tania Ferreira

While the decarbonization of aviation is seemingly one of the hardest engineering challenges of this century, the contribution from non-CO₂ effects should be also addressed, given that it leads to two-thirds of the aviation climate impact.

Contrail cirrus is estimated to be the biggest contributor to aviation’s climate impact, accounting for 56% of the effective radiative forcing. Furthermore, there is significant uncertainty in this estimate. Future hydrogen engines, albeit free from soot, will emit 2.6x more water vapor than Jet A engines, significantly increasing the potential for condensation trails (contrails). As a result, it is of critical importance to improve our understanding of contrail and subsequent contrail cirrus formation from future hydrogen aircraft; however, there are no available flight measurement data nor detailed simulations to inform these tools.

To this end, we have designed a novel project to quantify and reduce the climate impact of contrails from future hydrogen airplanes. We are currently adding features to a numerical code to simulate the formation of contrails. Our goal is to validate these features and develop the most representative set-up possible.

We are looking for a student enthusiastic about sustainable aviation and fluid dynamics to help us in the process of code validation and contrail simulation data post-processing and analysis. With our guidance, the student would be shortly introduced to the numerical simulation environment (Linux OS, HPC, C++ code), and would learn about our test case to be able to critically post-process and analyze its results. A general background on fluid dynamics and computer programming is advised for this research.

Skills/Interest/Background: Computer Programming, Engineering, Physics, Scientific Programming

Piecing together a Patagonian Puzzle: Using geochronology to understand the origin of the Andes

SESUR, SURGE
Category(s): Evolution of Earth
Department: Earth and Planetary Sciences
Mentor: Prof Stephan Graham, Mentor: Stephen Dobbs

The sedimentary record preserves the history of the world, from the rifting of oceans to the raising of mountains. In southern Patagonia, this record reveals the story of the breakup of the Gondwana supercontinent and the birth of the Andes. We have collected a series of rock samples that can detail missing parts of this history to better understand how the South American continent has evolved over time. This project provides a unique experience for undergraduates who will be able to work on an untouched area of Patagonian geology.

Students will get hands-on experience with processing rock samples for geochronologic age dating and will visit a state-of-the-art facility in Tucson, AZ where the analyses will take place. Students will also get the opportunity to learn geo-statistics using Python and Jupyter. No experience in Geology or Computer Science is required. Especially motivated students may have the opportunity to partake in a field season the following year in Southern Patagonia.

Skills/Interest/Background: Geology, Lab Work, Scientific Programming

Hunting for small earthquakes in the Bay Area

SESUR, SURGE
Category(s): Dynamic Earth, Evolution of Earth, Natural Hazards
Department: Geophysics
Mentor: Prof Greg Beroza, Mentor: Albert Leonardo Aguilar Suarez

The rise of high performance computing and artificial intelligence has enabled seismologists to find an order of magnitude more earthquakes than previously known, especially small ones that were hidden in noisy seismograms. This massive number of newly found earthquakes are providing insights into fault geometries, earthquake statistics, and the physics of faulting.

The vicinity of Stanford, the San Francisco Bay area is crossed by several major geological faults that constantly produce earthquakes. The iconic San Andreas fault is the boundary between the North American plate and the Pacific plate and has hosted major earthquakes in the past, the 1906 earthquake among them.

We propose to use Machine Learning techniques and empirical signal detectors to search for unknown earthquakes in the vicinity of Stanford. We are seeking for self motivated and independent learners with some experience in seismology and earthquakes. Coding skills in Python and shell scripting are preferred but not required. Students will be exposed and become familiar with forefront seismological research. The computations will be performed in a shared computing cluster. After assembling the earthquake catalog, this will be used to draw interpretations on the tectonic setting, patterns of seismicity and faults and interactions between populations of earthquakes.

Skills/Interest/Background: Computer Programming, Geology, Machine Learning, Mathematics, Physics, Scientific Programming

Reducing Greenhouse Gas Emissions Across the Food System: How On-farm Management Impacts Food-type Emission Factor Estimates

SESUR, SURGE
Category(s): Climate Change, Food and Agriculture, Human Dimensions and Sustainability
Department: Earth System Science
Mentor: Prof Rob Jackson, Mentor: Sierra Castaneda

Food systems account for roughly one-third of global anthropogenic greenhouse gas emissions, from agricultural practices to grow food, consumer diet choice, to food waste. Estimates of each stage of the food system’s contribution to overall GHG emissions are poorly constrained and highly variable due to differences in life cycle assessment methodology and geographic differences. Our group estimates GHG emissions and budgets across spatial and temporal scales. The overall goal of this research project is to use an interdisciplinary approachto advance our understanding of how we can reduce GHG emissions within our food system through improved agricultural management, sourcing, and diet choice. While reducing
emissions, we also aim to build a healthier, more delicious food system that better serves people
and the planet.

This research is conducted in partnership with community organizations throughout California, and can include field work, lab work, statistical analysis, and literature-based modeling, utilizing both quantitative and qualitative techniques to conduct research, and maintaining communication with community partners. There are a wide array of opportunities for undergraduate involvement and this research, and can vary depending on the student’s research interests and experience. The student has the option to focus on the agricultural-side of research, which includes conducting field work in agricultural settings as well as analyzing soil samples from the lab, and conducting interviews with farmers and agricultural workers. This vein of the research will also include data analysis and data visualization of results. Alternatively, students have the option to focus more on the mid to back-end of food-related GHG emissions, identifying and modeling mitigation pathways at the institutional and/or individual consumer level to reduce food-related greenhouse gas emissions.

Some examples of what a student summer project might look like:
-Students have access to the Stanford research farm/some of the community farm partners to develop a relevant research question around soil greenhouse gas emissions and/or sustainable agricultural management practices (i.e. cover cropping) and the impacts on carbon sequestration. Activities would include field work (collecting soil samples, taking soil flux measurements), lab work (preparing soil samples, measuring soil characteristics (carbon, nitrogen, water content), and analyzing data (graphing, statistical analysis, geospatial mapping).
-Students may use food-purchasing data from institutional partners to develop a research question related to the environmental impact of food (i.e. calculate emission estimates by food type and identify areas of improvement)

Students with interests in agriculture, greenhouse gas emissions, food systems, and nutrition are encouraged to apply. A background in earth sciences, data science, engineering, social science is helpful but not required.

Skills/Interest/Background: Chemistry, Computer Programming, Field Work, Lab Work, Statistics

Exploring Bacterial Cholesterol Production

SESUR, SURGE
Category(s): Evolution of Life
Department: Earth System Science
Mentor: Prof Paula Welander, Mentor: Alysha Lee

We are broadly interested in microbial lipids that double as fossil biomarkers. Geologists use these biomarker lipids to track the rise specific lineages and think about changing environmental conditions in deep time. By studying these compounds in modern day organisms, we hope to help better interpret their fossilized counterparts throughout the rock record. This project specifically focuses on cholesterol, a well characterized lipid essential to many eukaryotes. Previously, cholesterol was thought to be found only in eukaryotes and its fossilized counterpart used as a broad indicator for eukaryotes in the rock record. However, we have recently identified several bacteria capable of cholesterol production. While we know these bacteria produce cholesterol, little is known about the biosynthetic pathways governing production or the physiologic functions cholesterol performs in these bacteria.

Depending on student interest, this project can focus a couple of different aspects of the broad questions around bacterial cholesterol biosynthesis, such testing how different growth conditions impact cholesterol production or characterizing potential biosynthetic enzymes. Through this project, a student will have the opportunity to learn how to culture these unique bacteria, extract and analyze lipid data using gas chromatography mass spectrometry, and gain experience with molecular biology techniques including PCR and cloning. No previous experience with biological lab work is required, just a general interest and excitement for environmental microbiology.

Skills/Interest/Background: Biology, Chemistry, Lab Work

Developing machine learning techniques to model critical sea turtle habitats

SESUR, SURGE
Category(s): Climate Change, Human Dimensions and Sustainability, Ocean
Mentor: Prof Larry Crowder, Mentor: Michelle Maria Early Capistran

Endangered green sea turtles (Chelonia mydas) are ecosystem engineers with a key role shaping habitat structure and influencing nutrient flow in seagrass habitats, which provide critical ecosystem services. These areas are threatened by the synergistic effects of climate change and anthropogenic impact. Species distribution models (SDMs) are powerful tools for predicting species-specific habitat shifts under climate change. However, there are currently no SDMs that identify or predict green turtle occurrence, largely due to the lack of remotely sensed habitat datasets at adequate spatial scales and the high cost of animal tracking. We are developing an interdisciplinary approach to overcome these challenges by integrating multiple knowledge sources.

A critical aspect of our project is developing low-cost approaches to identifying and monitoring potential green turtle habitats in the California Current System by using machine learning to detect and classify seagrass (Zostera marina)—green turtles' preferred food in the northeast Pacific—in remotely-sensed satellite images. This will provide an accessible and cost-effective way to monitor, understand, and manage critical green turtle habitats under climate change.

Potential projects include acquiring and pre-processing satellite images of coastal areas in California and Baja California; developing open-source code (R or Python) to classify seagrass in satellite images; or mapping and analyzing seagrass distribution with the help of Geographic Information System (GIS) software such as QGIS. We will work with students to define a plan for summer research based on their interests and experience. We are seeking an enthusiastic student with a strong coding background (especially R or Python) and interest in remote sensing. GIS experience is a plus. Students from any field are encouraged to apply!

Skills/Interest/Background: Biology, Computer Programming, Machine Learning

Extraterrestrial speleology: Cave formation on Titan

SURGE
Category(s): Planetary Science
Department: Earth and Planetary Sciences
Mentor: Prof Mathieu Lapotre

The possibility of subsurface life has extended the boundaries of planetary habitability to the outer solar system. As windows into the subsurface, caves offer a prime exploration target to search for evidence of such life. They also enable access, and thus, the direct exploration of geological formations not exposed at the surface, providing unique insights into the geologic history of planetary bodies. Furthermore, caves often form from interactions between near-surface fluids and the planetary crust, and as a result, may preserve a record of hydrology and climate. The recent identification of putative solution caves on Titan – formed from the dissolution of organics-rich icy crust by methane and ethane – offer a promising avenue to probe the subsurface of Titan and decipher its geological, hydrological, and climate history.

In this project, our aim is to understand what the geometry of caves and subsurface conduits forming from the dissolution of Titan-like geologic materials could reveal about subsurface flow properties. Whereas cave geometry has been used on Earth to reconstruct past hydrological conditions, existing models that relate the flow of ground fluids, crust dissolution, and cave formation and evolution are specifically tailored to the dissolution of limestone from CO₂-rich fluids. As a first step towards modeling cave formation in Titan-like materials, the models need to be generalized to non-CO₂driven dissolution.

To that end, we anticipate conducting a brief field campaign in a gypsum cave, with the goal to survey the cross-sectional geometry of the cave conduit using lidar technology and to collect samples for lab analyses. The student will participate in the field campaign along with the mentor and collaborators from NASA JPL. Back on campus, the student will generate 3D models of the cave walls to measure cross-sectional geometry as well as analyze collected samples through grain-size characterization and, possibly, microscopy. Upon completion of field-data analysis and if time permits, the student could also get involved in the initial stages of numerical modeling. Prior experience in speleology, lab analyses, and/or modeling are not required.

Skills/Interest/Background: Computer Programming, Field Work, Geology, Lab Work, Physics, Scientific Programming

Remote sensing in agriculture

Category(s): Food and Agriculture, Human Dimensions and Sustainability
Department: Earth System Science
Mentor: Prof David Lobell

Hundreds of millions of smallholder farmers around the world face challenges of climate change and inadequate soil nutrition. In addition, many ecosystems continue to be stressed by the effects of local agricultural systems, either through land use conversion or nutrient and pesticide runoff. This project will work towards improving datasets used to study and inform management in these systems, with an emphasis on using new satellite sensors. Among the potential specific topics are: (i) mapping global sugarcane areas at high resolution using lidar and optical data, (ii) mapping the effects of wetter springs on soil ponding and failed crop germination, and (iii) mapping adoption and impacts of soil and water conservation practices in Eastern and Southern Africa.

The specific project will be decided closer to the summer based on student interests and data availability. This is a good project for students with a strong coding background (especially R or python) and a desire to gain familiarity with remote sensing data and methods.

Skills/Interest/Background: Computer Programming, Machine Learning, Statistics

Using pressure to design better materials for energy applications

SESUR, SURGE
Category(s): Energy
Department: Earth and Planetary Sciences
Mentor: Prof Wendy Mao, Mentor: Anna Celeste

The global climate and energy crisis demands alternative ways to generate and supply energy. New materials with exceptional properties are crucial to developing sustainable energy technologies. Transition metal perovskite chalcogenides are emerging semiconductors with rich tunability and functionality for a wide range of optoelectronic and photonic applications. Applying an external pressure is a powerful way to finely tune the structural and electronic properties of these materials as well as modify chemical bonds. With this approach, it is possible to study and optimize materials properties for guiding the development of future green energy applications.

In this project, the student will perform high-pressure experiments on transition metal perovskite chalcogenides exploiting a diamond anvil cell combined with in situ characterization techniques such as Raman spectroscopy and X-ray diffraction. These measurements will reveal changes in the structure of the material as function of pressure in order to better understand the mechanisms governing the structure-properties relationship in these materials.

We are looking for an engaged and enthusiastic student who will take initiative in learning new analytical techniques and applying this knowledge to their research. The project will involve collecting, analyzing, and interpreting Raman and X-ray measurements with the support of the mentor. No prior Earth science knowledge is required but background or training in materials science and chemistry is desirable.

Skills/Interest/Background: Chemistry, Geology, Lab Work, Physics

Toxic metals in soil nanoparticles during and after wildfires

SESUR, SURGE
Category(s): Climate Change, Human Dimensions and Sustainability, Natural Hazards
Department: Earth System Science
Mentor: Prof Scott Fendorf, Mentor: Dr. Alireza Namayandeh, Mentor: Dr. Alondra Lopez, Mentor: Dr. Claudia Avila

Wildfires are increasing in frequency and severity globally, as seen in the western U.S., and can impact the formation, transformation, and dispersion of nanoparticles (<30-nm diameter) in smoke, post-fire dust, and water. Because of their extremely small size, high surface area, and high reactive surface sites, nanoparticles control the (im)mobilization of contaminants and nutrients in soil and water; they also pose a threat to human health, primarily through inhalation. We are interested in deciphering the role of fire-altered soil nanoparticles on the environmental fate of toxic metals and their persistence in post-fire landscapes. Understanding metal transformations during wildfires and their susceptibility to post-fire dispersion will be necessary to evaluate and mitigate possible post-fire metal exposure, particularly in local and distal communities.

Characterization of natural nanoparticles is challenging due to their extremely small particle size, disorder structure, and metastability. We will study the association between toxic metals and nanoparticles from natural and lab-generated particulates using a range of advanced characterization techniques, including synchrotron radiation methods, transmission and scanning electron microscopy (TEM and SEM), and aqueous chemical analyses. We are looking for one or two motivated undergraduate students to help with various aspects of the project involving soil sample collection, preparation, and characterization. A background in mineralogy, soil science, and/or chemistry is helpful but not required.

Skills/Interest/Background: Chemistry, Field Work, Lab Work

Applying AI to understand Agroforestry at Scale

SESUR, SURGE
Category(s): Climate Change, Food and Agriculture, Human Dimensions and Sustainability
Department: Earth System Science, Department: Emmett Interdisciplinary Program in Environment & Resources
Mentor: Prof David Lobell, Mentor: Siddharth Sachdeva

Millions of smallholder farmers in the global south are already using climate smart practices such as agroforestry. However, our understanding of the climate mitigation and adaptation benefits and ecosystem services provided by these agroforestry systems is still limited. This project will work towards improving datasets used to study and inform management in these systems for carbon sequestration and climate adaptation, with an emphasis on using new satellite sensors. Among the potential specific topics are: (i) detecting individual trees in agricultural landscapes to understand tree density (ii) classifying tree species using temporal and multispectral data to understand tree crop biodiversity and carbon sequestration (iii) predicting tree height directly from imagery to measure tree survival rates and carbon sequestration. The specific project will be decided closer to the summer based on student interests and data availability.

The project will involve collecting and pre-processing the satellite images, leading teams of annotators to conduct ground-truth evaluation on the predictions, and if there’s interest, applying deep learning models to this imagery. Students with a strong work ethic and attention to detail are encouraged to apply. Coding skills in Python or Javascript are preferred.

Skills/Interest/Background: Computer Programming, Machine Learning, Scientific Programming, Statistics

Redox change during Earth’s middle age - FILLED

SESUR
Category(s): Dynamic Earth, Evolution of Earth, Evolution of Life
Department: Earth and Planetary Sciences
Mentor: Prof Erik Sperling, Mentor: Lucy Webb

A student for this project has been found.

A major goal in historical geobiology has been tracking how oxygenation of the oceans and atmosphere has changed through geological time. In particular, geochemists have worked to test hypotheses that oxygen levels rose dramatically ~2300 Ma (the Great Oxidation Event or GOE) and around the Ediacaran-Cambrian boundary (the Neoproterozoic Oxygenation Event or NOE). Many researchers have further considered the NOE to be the main causal driver of the Cambrian ‘explosion.’ Critical to understanding changes in oxygen levels through time is more detailed knowledge of the initial conditions during the Mesoproterozoic (1600-1000 million years ago), prior to the rise of animals. Using both laboratory and statistical analyses, this project will involve testing how the redox landscape of the ocean changed through these critical intervals.

The student will be responsible for laboratory analyses of the iron, carbon, sulfur, and trace metal contents of sedimentary rocks from key stratigraphic successions—primarily the Mesoproterozoic Pinguicula Group and early Neoproterozoic Dolores Creek Formation (both from Yukon) and lower Cambrian succession from Montana. The student will interpret geochemical proxies from these successions to understand likely paleoenvironmental conditions during deposition. The student will then compile these data with a major new data compilation provided by the Sedimentary Geochemistry and Paleoenvironments Project (SGP) to track the redox landscape of the oceans, specifically tracking the abundance of redox-sensitive trace metals in anoxic shale. This will result in a new understanding of how ocean conditions changed with respect to key events in animal evolution. Overall, this project will result in an understanding of 1) general laboratory methodologies that will be applicable to any future lab work, 2) geochemical proxy interpretation, 3) Earth’s deep-time history, and 4) statistical analyses of large datasets using the R programming language, applicable to future scientific data analysis.

The project can also include fieldwork to Mesoproterozoic or Cambrian rocks in Yukon or Montana. Our preferences is for a student that has taken at least two classes in Geological Sciences and is ideally majoring or minoring in Geological Sciences (or is planning to).

This project will be part of a group project to understand how paleoenvironmental conditions on Earth have changed through time, and the relationship between these environmental changes and the evolution of plant and animal life. Although all students will have their own discrete projects, we will work as a team to learn laboratory techniques, understand geochemical proxy interpretations, develop analytical tools in R, and finally analyze new data in the context of data collated by our international research consortium, the Sedimentary Geochemistry and Paleoenvironments Project (https://sgp.stanford.edu; which the student will be able to join).

Skills/Interest/Background: Chemistry, Field Work, Geology, Lab Work, Scientific Programming

Tracking the effects of early land plants on the Earth system

SURGE
Category(s): Climate Change, Dynamic Earth, Evolution of Earth, Evolution of Life
Department: Earth and Planetary Sciences
Mentor: Prof Erik Speriling, Mentor: Emily Ellefson, Mentor: Hunter Olson

The diversification and geographic spread of plants on land is one of the most profound changes in the history of our planet. Modern Earth is covered by lush tropical forests, seemingly endless grasslands, and soaring redwoods—in striking contrast to Precambrian landscapes that consisted largely of bare rock and microbial mats. Climatic changes, especially in the Devonian, have long been linked to plant evolution. Nevertheless, there are few robust constraints on the net impact of changes mediated by the emergence of land plants or the tempo with which these occurred. Two of the most fundamental—and most debated—aspects of how plants transformed our planet concern potential changes in long-term nutrient cycling and oxygen levels, both on land and in the oceans. Using both laboratory and statistical analyses, this project will involve testing how changes in the redox landscape (oxygen contents) of Earth’s oceans correlates with the evolution of land plants.

The student will primarily be responsible for making laboratory organic carbon isotope measurements and total organic carbon measurements from a new stratigraphic section of the Road River Group and McCann Hill Chert from Alaska that spans the critical Ordovician through Devonian interval. These analyses will help develop an age model for the succession, as well as track changes in organic carbon burial through time. Once the age model is developed, the student will be responsible for analyzing trace metal data from the succession, specifically testing the hypothesis that the oceans became more oxygenated coincident with the evolution of the first plants having moderately deep rooting systems. Finally, the student will combine these new data with a major new data compilation provided by the Sedimentary Geochemistry and Paleoenvironments Project (SGP) to test this hypothesis on a global scale. Overall, this project will result in an understanding of 1) general laboratory methodologies that will be applicable to any future lab work, 2) geochemical proxy interpretation, 3) the evolutionary history of plants, and 4) statistical analyses of large datasets using the R programming language, applicable to future scientific data analysis.

We are ideally looking for someone majoring in Geological Sciences or related fields, although there are no prerequisites aside from interest in the project!

Skills/Interest/Background: Biology, Chemistry, Geology, Lab Work, Scientific Programming

Modeling dengue virus transmission dynamics in Cambodia under changing climate scenarios

SESUR
Category(s): Climate Change, Human Dimensions and Sustainability
Department: Biology, Department: Emmett Interdisciplinary Program in Environment & Resources
Mentor: Prof Erin Mordecai

Dengue virus (DENV) is a mosquito-borne flavivirus endemic to many tropical and subtropical regions of the world. Transmission to human populations occurs through the bites of infected Aedes aegypti and Aedes albopictus mosquitoes after an infectious blood meal. Impacting an estimated 100-400 million people a year, Dengue remains one of the most serious causes of illness in many Asian countries. As a persistent virus in Cambodia, Dengue cases primarily spike during the rainy season (May-November) with large outbreaks of one or more antigenically unique viral serotypes (DENV-1, -2, -3, -4) occurring every 2 to 4 years. Although the majority of worldwide Dengue cases are generally asymptomatic, people infected with Dengue can become susceptible to severe Dengue, a result of repeated Dengue infection. Initial Dengue infection can cause high fever and mild flu like symptoms, while secondary infections with different viral serotypes can lead to more fatal health outcomes, including hemorrhagic fever and organ failure.

While pre-existing research suggests an association between increasing global temperatures, changing precipitation patterns, and rising cases of mosquito borne diseases, little is known about the potential impacts of climate change on Dengue in Cambodia. This project seeks to address these concerns by creating future projections of Dengue burden in Cambodia under varying climate change scenarios. By using remotely-sensed climate data and information on Dengue transmission patterns unique to Cambodia, this work will use mechanistic modeling and machine learning frameworks to better understand the impacts of climate change on mosquito-borne infectious disease transmission in low income settings.

We are seeking a student researcher who is interested in studying the intersections of climate change and infectious disease dynamics and is passionate about designing computational research that can help optimize real-world solutions. If time allows, this project will also model the potential benefits of introducing wolbachia–parasitic microbes with pathogen blocking capabilities–into wild mosquito populations to simulate how the novel intervention could be used to reduce Dengue transmission in Cambodia.

Skills/Interest/Background: Biology, Computer Programming, Machine Learning, Scientific Programming, Statistics

Working the core: using ancient DNA to extract information about insects, and how we control them

SESUR, SURGE
Category(s): Climate Change, Evolution of Life, Food and Agriculture
Department: Biology, Department: Earth System Science
Mentor: Prof Liz Hadly, Mentor: Dr Kirsten Verster

Metabarcoding allows for the genetic identification of many taxa within a given sample (known as eDNA) by utilizing taxa-specific ‘barcodes’ with modern next-generation sequencing technologies, in order to process millions of reads in parallel. eDNA shows promise as a high-throughput way to study biodiversity at different scales.

Global biodiversity is threatened by anthropogenic disturbance, and is projected to lead to the extinction of thousands of species over the next 100 years. Insects are no exception – declines in insect diversity and abundance have been widely documented at local, regional and global scales, giving rise to the controversial “Insect Apocalypse”. However, records of insects over time are biased towards collection of charismatic or economically important taxa, and are temporally and spatially limited. The postdoctoral fellow mentor (Dr. Kirsten Verster) will use paleoecological methods with emerging sedimentary ancient DNA (sedaDNA) techniques to assess changes in insect abundance and richness over time, and, more specifically, in response to pesticides (and, potentially, other anthropogenic disturbances). Dr. Allison Stegner of the Hadly Lab has collected sediment cores that date back at least 1200 years, which were collected from a marsh and hydrologically connected reservoir at Jasper Ridge Biological Preserve (JRBP). Preliminary trials of DNA extraction methods and subsequent Nanopore sequencing of DNA extracted from core samples (conducted by Dr. Sergio Redondo) are promising: core samples about 100 years old identified 38 arthropod taxa.

The student will be conducting an important analysis that ties into this project: detecting bacterial pesticides in ancient core samples using the same sedaDNA principles. Our lab has records of several types of biological pesticides which have been applied to JRBP over the years. The student will evaluating methods of detecting these biological pesticides (which can include the common pesticides Bti and Ls) using molecular biology on ancient DNA samples. Students will learn, either in practice or in theory, basic principles of the following topics: molecular biology; sedaDNA; PCR and RT-qPCR; primer design; next-generation sequencing (in particular Nanopore) technology; designing and executing an independent project; among others.

Students are expected to be intellectually motivated, driven to understand the natural world, and be painstakingly careful. Perfection is not expected but honesty - about your understanding, about mistakes, etc;. - is crucial. No prior experience is expected though introductory labwork or courses in biology and genetics may prove helpful. I strive to have a symbiotic relationship with the student, providing guidance, training and mentorship in exchange for a fellow collaborator who is also working toward a common goal.

Skills/Interest/Background: Biology, Chemistry, Field Work, Lab Work

Toxic Soilscapes: Measuring and Mapping Metals in Urban Environments

SURGE
Category(s): Food and Agriculture, Human Dimensions and Sustainability
Department: Earth and Planetary Sciences
Mentor: Prof Jane Willenbring, Mentor: Omar Rosales Cortez

Demographics between communities vary widely nationwide and even between cities, towns and neighborhoods. Disparities between communities appear in various forms including the levels of toxic pollution from a legacy of urban contamination, representing one of many examples of environmental injustice in the United States.We have over a decade of experience working with communities to provide screening of soils for heavy metal pollution such as lead (Pb), cadmium (Cd), and arsenic (As). Our group aims to work with local communities in East Palo Alto and nearby cities, by equipping them with knowledge of levels of heavy metal pollutants within their respective communities.

This project provides a wide variety of opportunities for research and engagement and is conducted through collaborations with community organizations around the Bay Area. Current/past work in East Palo Alto in 2022 made use of various samples brought to our Farmers Market booth by community members.

We will work with the student to outline a plan that builds on our past and ongoing networks with local communities and the student’s strengths. We aim to expand the student’s technical skillset around environmental justice topics. Tools used could include but not be limited to, a handheld XRF, geographic data science, and laboratory procedures that utilize acids. The student will help choose the specific project and steer how the outcome and results will be shared with the community.
Interested students with a background in Earth science or environmental health science looking to work with people in local Bay Area communities should apply. Prior lab experience is not required. Students who can speak and write in Spanish are highly encouraged to apply.

Skills/Interest/Background: Chemistry, Field Work, Lab Work, Statistics

Worldwide WORMS: Unearthing Secrets in the Soils

SESUR
Category(s): Climate Change, Dynamic Earth, Food and Agriculture, Human Dimensions and Sustainability
Department: Earth and Planetary Sciences
Mentor: Prof Jane Willenbring, Mentor: Adrian Wackett

Parts of Earth are being invaded by… earthworms! What kinds of physical and chemical changes to soils and carbon stocks should we expect as worms invade boreal forests and thawing-permafrost landscapes? How can we use gradients of earthworm densities to constrain the impact of earthworms on tropical carbon stocks and rates of soil production and soil erosion.

Our lab group works to understand the linkages between life and landscape. We use geochemical techniques, topographic data, soil surveys and field observations to understand the landscapes surrounding us. Projects for summer research can be related to earthworm impacts on soils from the El Yunque National Forest, Puerto Rico, northern Alaska, and even worms in the lab. We anticipate working with the student to craft a project together that focuses on the student’s interests and builds technical competencies and lab skills. Students with an interest in Earth and planetary sciences or Earth systems science are preferred. Prior lab experience is not required.

Skills/Interest/Background: Biology, Chemistry, Field Work, Geology, Lab Work, Physics, Statistics

Greenhouse gas emissions from contaminated rice paddies: from environmental geochemistry to environmental justice

SESUR, SURGE
Category(s): Climate Change, Food and Agriculture
Department: Earth System Science
Mentor: Prof Scott Fendorf, Mentor: Dr. Alireza Namayandeh, Mentor: Aria Duncan

Rice paddies are one of the largest sources of atmospheric methane, leading to increased global warming. Developing an understanding and ability to manage processes that restrict methane production within rice cropping systems is therefore critical. A primary means to limit methane emissions is by restricting methanogen (the organisms responsible for methane production) activity either through microbial competition or by restricting their food sources. An exciting opportunity arises by managing iron cycling within rice paddies, particularly through the formation of small, rust-like particles known as ferrihydrite. Ferrihydrite is an iron oxide nanoparticle widespread in soils, sediment, and water. In aqueous environments such as rice paddies, ferrihydrite shows a high affinity for interaction with organic matter that serves as a food source for methanogens. Natural groundwater used for rice irrigation can contain nutrients and contaminants such as arsenic, phosphate, and nitrate. These nutrients/contaminants compete with organic compounds for adsorption on the surface of ferrihydrite, affecting the production of greenhouse gases. We plan to simulate the chemical conditions of flooded rice paddies in greenhouses and study the coupled interactions of ferrihydrite nanoparticles, organic compounds, and nutrients/contaminants to understand how these reactions control greenhouse gas emissions.

The other aspect of this project is to integrate environmental justice into our research. Climate change, intensified by greenhouse emissions from rice paddies, is arguably the most critical environmental and social problem and the greatest threat to global security, impacting the lives of many around the world with disproportionate impacts on underrepresented groups. It can destabilize the livelihoods of certain communities through extreme weather, rising sea levels, droughts, wildfires, desertification, and floods. We will use art to address the social aspect of our research by holding visual art workshops and producing short plays. Arts integrated with science can be very powerful tools to promote civil discourse around climate change issues, enhancing the efficacy of our research.

We are looking for a motivated undergraduate student to join our team and help with the various aspects of this project, involving nanoparticle synthesis, wet lab chemistry, aqueous chemical analyses, and environmental justice workshops. A background in mineralogy, soil science, chemistry, and art is helpful but not required.

Skills/Interest/Background: Chemistry, Lab Work

Impact of Building Design on Wellbeing

SURGE
Category(s): Built Environment, Human Dimensions and Sustainability
Department: Civil & Environmental Engineering
Mentor: Prof Sarah Billington, Mentor: Basma Altaf, Arash Tavakoli, and Eva Bianchi

Human well-being is closely tied to the environments we evolve in, which include the built environment. Our research focuses on studying the role of building design in impacting human health and wellbeing from several angles. The following are some of our projects:

Exploring VR for Design Intervention Studies

This project aims to facilitate time- and cost-effective testing of design interventions to promote wellbeing to identify the promising variables to explore more deeply through lab experiments. Work scope would range from building models using BIM, coding in Unity, testing the VR environment with human subjects as well as analyzing the data collected. Experience working with R, Revit and Unity software is preferred but not necessary.

Biophilic Illusions

This project aims to use physical-digital representations of nature to augment building interiors using elements from ambient nature in order to promote occupant connectedness to nature and well-being. Work scope would include building physical and/or digital prototypes of biophilic illusions as well as carrying out testing with human subjects. Prior experience working with microcontrollers (Arduino, ESP 32) and R is preferred but not required.

Skills/Interest/Background: Engineering, Field Work, Lab Work, Machine Learning, Statistics

Naturally occurring metals in groundwater: predicting their extent and biogeochemical controls

SESUR, SURGE
Category(s): Climate Change, Freshwater, Human Dimensions and Sustainability
Department: Earth System Science
Mentor: Prof Scott Fendorf, Mentor: Dr. Alandra Lopez, Mentor: Dr. Alex Honeyman

Communities globally are faced with challenges in access to safe drinking water, a stress that is further strained by prolonged droughts and groundwater overuse. Low-income and marginalized communities in rural settings are disproportionately burdened by water problems, often relying on groundwater from unregulated private wells. The widespread presence of naturally occurring, or geogenic, metals and metalloids in soil and sediments represent a major threat to groundwater quality. A primary concern is arsenic, which occurs in nearly all sediments at trace levels and can be mobilized into water under various geochemical conditions. Groundwater arsenic contamination in South and Southeast Asia, for example, has led to the largest mass poisoning in history. Having the capability to spatially resolve the potential of geogenic contaminants to degrade water quality and understand the environmental factors that drive their release from soil and sediments into water is crucially needed.

In this project, our goal is to decipher the climate and geochemical controls on regional groundwater contamination of naturally occurring metals and metalloids, particularly arsenic, in the San Luis Valley, Colorado. The San Luis Valley is a rural agricultural area reliant on groundwater for drinking water. In both private and public wells, arsenic concentrations have ranged from less than 2 to 150 μg/L between 1986 and 2014 with 26.8% having arsenic levels greater than 10 μg/L, its maximum contaminant level. We will incorporate laboratory chemical analyses of groundwater samples collected across the San Luis Valley into geospatial assessments using publicly available historical data of groundwater arsenic and other environmental factors.

We are seeking a student who will (1) learn laboratory chemical measurements, including pH, trace metals, and nutrients, using a variety of analytical instruments, (2) develop skills in data analysis and interpretation, and (3) will have the opportunity to make geospatial predictions of groundwater contamination using GIS and R. No previous laboratory, GIS or R knowledge/experience required, just willingness and motivation to learn!

Skills/Interest/Background: Chemistry, Geology, Lab Work, Machine Learning, Scientific Programming

Plate tectonics beneath the southeast Himalaya from seismic data

SESUR, SURGE
Category(s): Dynamic Earth, Natural Hazards
Department: Geophysics
Mentor: Simon Klemperer, Mentor: Xiaohan Song

Plate convergence between the Indian plate and the Eurasia plate beneath the southeast Himalaya has led to rich near-Moho seismicity. Local crustal tectonics is complicated by interactions between north-directed subduction of India beneath Tibet, east-directed subduction of India beneath Burma, the intervening Shillong plateau uplift, and strike-slip faults that may extend into the mantle. As a result, the origin of the near-Moho seismicity remains uncertain. Moho geometry is crucial in determining the origin of local near-Moho earthquakes, but existing Moho models in this region are incomplete or poorly constrained so a systematic study is needed across the High Himalaya and the Indian plain.

The student will review existing publications and access available local station data for the southeast Himalaya and northeast India, and calculate receiver functions to get Moho depths. The student will likely participate in additional studies of the near-Moho earthquakes (e.g. measuring corner frequencies, calculating Gutenberg-Richter statistics) to better understand their tectonic setting. Depending on availability of data, and the student’s facility with computational tools, the intern may also work on improving our regional Moho map of Tibet and the Himalaya.

Skills/Interest/Background: Computer Programming, Geology, Physics, Scientific Programming