Stanford University
SESUR student group

Potential Projects for Summer 2021

SESUR applicants - Stanford Students

If you are interested in learning more or getting involved in one of these projects, you should contact the faculty member  and other mentors directly.  This list is not comprehensive however, and many other projects are possible.  Please visit this page often for project updates.  Also, feel free to explore all our faculty research areas and contact anyone whose research interests you.  For your reference, you can also view the project archives at the bottom of this page for an overview of previous year's submitted projects.

SURGE applicants - Non-Stanford Students

If you are interested in getting involved in one of these projects, please indicate so on your application. This list is not comprehensive however, and many other projects are possible. Feel free to browse the list of faculty research interests and indicate, on your application, anyone whose research interests you.

last updated on 12/11/2020

Potential Projects for Summer 2021

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

SESUR, SURGE
Category(s): Climate Change, Evolution of Earth
Department: Geophysics

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.
Summer only.

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

Studying the subsurface response to fluid extraction and injection at wells via the integration of InSAR-measured surface deformation and well data

SESUR, SURGE
Category(s): Dynamic Earth, Human Dimensions and Sustainability
Department: Geophysics


Humans continually alter subsurface behavior by extracting and injecting fluids at wells (e.g. groundwater and oil/gas pumping; CO2 storage and wastewater disposal). These activities can have important consequences that affect local environments and communities, such as induced earthquakes, permanent compaction of aquifers, or deformation that can damage nearby infrastructure. To mitigate these effects, it is vital to monitor and understand the subsurface response to well activity, allowing us to model and predict future behavior. 

Our group is assessing the use of interferometric synthetic aperture radar (InSAR) for measuring (from SPACE!) and using the evolution of surface deformation to infer the subsurface response to various types of well activity. In this project, there is space for students with a large variety of backgrounds and interests, including signal processing, geomechanical modeling, or integration and analysis of large data sets. Though the project will be related to the application of InSAR to induced seismicity and/or subsurface fluid flow, it has the flexibility to be student-driven. Depending on research interests, it may be beneficial to have programming experience (e.g. Matlab or Python), though the only requirement is an enthusiasm to learn more about radar remote sensing and its applications!  Summer only. 

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

Human Dimensions of using Marine Environmental DNA to Monitor Ocean Biodiversity

SESUR
Category(s): Human Dimensions and Sustainability, Ocean
Department: Emmett Interdisciplinary Program in Environment & Resources


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 actually represent. In order to advance the use of marine eDNA, we need a lot of scientific work, but we also need a better understanding of how scientists, policymakers, and the public think about the promises and pitfalls of the technology. Looking at how eDNA is discussed in the media provides one window into how people perceive eDNA.

This collaborative project will involve systematically identifying media articles about marine eDNA, categorizing and recording the kind of information included in the articles, and analyzing that information to better understand how journalists depict the potential uses of marine eDNA. Research collaborators will learn more about the science of marine eDNA, gain experience with qualitative/quantitative content analysis, and if interested, contribute to drafting a manuscript on the project findings. There are no required qualifications for this position, but you would be an especially good fit if at least one of the qualifications below applies to you:

  • Excitement to learn more (and read a ton of articles) about marine environmental DNA
  • Experience conducting a large literature review
  • Interest in environmental communication
  • Experience with statistical analysis

If you are interested in the human dimensions of marine environmental DNA but not the particular project outlined, there may be opportunities to design or contribute to other related projects; please don’t hesitate to reach out.

Spring preferred.  Maybe Summer.  Meghan may be on a research cruise for a good chunk of the summer (COVID-dependent), in which case would likely not be able to mentor a student over the summer. 

Skills/Interest/Background: Biology, Engineering, Statistics

Fe-bearing colloids in anoxic sediments: How do they form? Are they mobile? And do they transport metal contaminants?

SESUR, SURGE
Category(s): Freshwater, Natural Hazards
Department: Earth System Science
Mentor: Scott Fendorf, Mentor: Maya Engel


Fe-bearing colloids are commonly found within anoxic sediments of gravel bed floodplains. These colloids may bind metal contaminants and organic compounds, influencing their reactivity and mobility. Changes in biogeochemical conditions, such as shifts in the groundwater table level and consequently in the flux of oxygenated water, may further impact the fate of the colloids. To date, the mechanisms driving Fe-bearing colloid generation are largely unknown. Thus, our main objective is to advance our understanding of Fe-bearing colloid formation, chemistry and transport.

Our project will examine the formation and behaviour of Fe-bearing colloids at oxic-anoxic interfaces. Specifically, we will investigate the mechanism of colloid generation, how varying biogeochemical conditions influence colloid stability and mobility, and whether metal contaminants incorporate into the colloids.

As a summer intern, you will assist in setting up systems in the lab to monitor the colloidal activity. You will help sample, prepare, and analyse both aqueous and solid samples of the colloids. During the internship you will learn basic lab skills as well as how to use a suite of analytic instruments that will be repeated several times (allowing you to master the skills and become confident with the work). The work will be conducted both at the Department of Earth System Science and at SLAC National Laboratory with postdoc Maya Engel and staff scientist Kristin Boye. This is a great opportunity for students interested in basic environmental/analytical chemistry.

Skills/Interest/Background: Chemistry, Lab Work

That Sinking Feeling: Modelling Land Subsidence in California's Central Valley

SURGE
Category(s): Climate Change, Dynamic Earth, Food and Agriculture, Freshwater, Human Dimensions and Sustainability, Natural Hazards
Department: Geophysics
Mentor: Rosemary Knight, Mentor: Matthew Lees


On less than one percent of the total farmland in the United States, California’s Central Valley produces eight percent of the nation's agricultural output by value. However, the Valley has an arid climate, and a significant portion of the water required for irrigation comes from groundwater pumping. The scale of this groundwater pumping has caused severe environmental issues in the Valley; one of the most acute of these is the sinking of the land surface, known as land subsidence. In places, subsidence rates have exceeded 20 cm/year, causing millions of dollars of damage to infrastructure such as canals and railways. Mitigating this subsidence is a critical issue in the Valley.

We are looking for a student to run computer simulations of land subsidence. The simulations will explore some of the details behind how and why subsidence is occurring, and how it might continue into the future. This project will be best suited to a student with background in physics and mathematics. Although training will be provided to run the computer simulations, coding experience (in any language) is desirable as the project is computational in nature. The student will gain valuable skills working with data and running physical models, as well as an insight into how physical modelling can be used to provide critical insight into environmental issues.

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

Understanding satellite measurements of vegetation water content for improved wildfire prediction and monitoring of vegetation health

SURGE
Category(s): Climate Change, Natural Hazards
Department: Earth System Science
Mentor: Alexandra Konings, Mentor: Nathan Dadap, Mentor: Krishna Rao


Large wildfires and forests die-offs are occurring with increasing frequency and severity, highlighting the negative consequences of a changing climate. While much work has been done to understand and predict how droughts cause these events, there has been relatively little research about the impact of hydrologic conditions at the land surface. Our recent findings suggest that vegetation water content plays a significant role in mediating these events. Unlike many other relevant variables, vegetation water content can also be measured directly with (microwave-frequency) satellites. Given the unparalleled spatial and temporal coverage afforded by satellite measurement, these datasets have enormous potential for monitoring fire risk and forest health. However, many questions remain regarding how to interpret these measurements and their accuracy.

In this project, the student will have an exciting opportunity to compare datasets related to vegetation water content derived from various satellite products, with the end goal of contributing an improved understanding of the information that these datasets can provide as well as their limitations. If progress allows, this research could be presented at research conferences and/or through journal publication. The ideal candidate will have experience manipulating data using a programming language such as Python, R or Matlab. Background knowledge regarding wildfires or ecohydrology are a plus, though not required. We seek candidates with a strong interest in learning analytical skills applicable to data analysis in earth science.

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

Exploring Community Action to Address Sustainability Issues

SESUR, SURGE
Category(s): Climate Change, Human Dimensions and Sustainability
Department: Emmett Interdisciplinary Program in Environment & Resources
Mentor: Nicole Ardoin, Mentor: Anna Lee, Mentor: Mele Wheaton, Mentor: Alison Bowers


Issues such as climate change and the COVID-19 pandemic emphasize the complexity and interconnectedness of the global community, particularly the ways in which collective action is required for effective solutions to such issues. In this project, we seek to understand more deeply how to foster as well as measure collective environmental literacy in support of community action to address sustainability issues. Currently, we are developing approaches and tools to measure collective environmental literacy, with an emphasis on instruments that can be administered remotely. We will begin pilot testing such approaches and measures in the winter and spring quarters 2020-21, with data collection and analysis continuing  into the summer.
 
This is a great opportunity for students interested in ideas related to environmental social science, collective and community-scale action, motivations for and  barriers to civic engagement, and larger-scale sustainability issues. Students will have a chance to develop skills in survey development and administration, conducting interviews, analyzing survey and interview data, developing literature reviews, and academic writing. We seek students from a range of backgrounds and experiences, including especially those with a background and/or some experience in the social sciences background. We also welcome those from more of a natural science or engineering background, but who have interest in the social sciences as well as those just beginning to explore the environmental and sustainability sciences.

Our lab is highly collaborative and fast-paced; respectful, kind, and constructive in interactions; and seeks team members with a diversity of perspectives, interests, and life experiences. We also seek people who are independent, demonstrate a commitment to quality and rigor, and are curious and energetic in their pursuit of environmental social science.
Spring and Summer

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

Linking models and data to understand the terrestrial carbon cycle

SESUR, SURGE
Category(s): Climate Change
Department: Earth System Science


The carbon cycle is an essential part of life on Earth. With global models of the carbon cycle, we can make predictions of the fate of the terrestrial biosphere under climate change, which both help to predict what ecosystems might look like in the future, and even can help us improve our estimates of changing temperatures and rainfall. However, in practice, predictions of the future carbon cycle are often highly uncertain due to the complexity and variability of the Earth system. One way to improve carbon cycle models is by using observed data to constrain the model parameters that control flows of carbon between different pools, thereby updating the model to best reflect reality. This method of optimally combining theory with observations is called model–data fusion. Model–data fusion is especially effective for global carbon cycle models because of recent developments in the quantity and quality of relevant satellite remote sensing data available for ingestion. Our research group uses one such model–data fusion system—the CARbon Data MOdel fraMework (CARDAMOM)—in different ways to better understand what these observations can tell us about model processes, parameters, and predictions. CARDAMOM is a flexible framework that can be customized by the user.

We seek a motivated student interested in applied scientific programming and data analysis. Advised by Caroline Famiglietti and Alexandra Konings, the student will use CARDAMOM to help understand and improve carbon cycle prediction accuracy. A range of available projects are available depending on the student’s interests, from model development to data analysis. While a background in earth sciences is not required, the student should have some prior experience with C and/or Python, as well as with working at the command line.
Spring or Summer

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

Integrated kinetic energy of a mature tropical cyclone in a variety of climates

SESUR
Category(s): Climate Change
Department: Earth System Science


A tropical cyclone is a general scientific term describing hurricanes and typhoons.  The intensity of the surface winds of a tropical cyclone is highly relevant to its impacts when it makes landfall. How does this intensity vary with climate change? The integrated kinetic energy of a tropical cyclone acts as a measure of how intense the surface wind field is, and so understanding how this quantity may vary with different climate variables is important to predicting how the intensity of tropical cyclones may behave in future climates. In this work, we will use integrated kinetic energy as a tool to investigate how various climate variables affect tropical cyclone intensity. 

This project will involve quantifying how the integrated kinetic energy of simulated, idealized tropical cyclones is affected by changes in a variety of climate variables, such as sea surface temperature and atmospheric moisture content. With guidance from research mentors, the student will design different setups of a simple model to produce a suite of simulated tropical cyclones under different climates. The student will additionally calculate the integrated kinetic energy of these tropical cyclones to tackle the leading research question, and will interpret the physics behind the results.  

We are seeking an enthusiastic student with an interest in the physics of atmospheric flows to tackle this project involving computational analysis and working with numerical models. Knowledge of calculus and basic programming (in any language) is required. No atmospheric science experience is necessary! However, I will likely send you a bit of background reading on atmospheric science to do before the project starts. 
Summer only.

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

Computer Simulations of Earthquakes and Volcanoes

SESUR, SURGE
Category(s): Dynamic Earth, Natural Hazards
Department: Geophysics
Mentor: Eric Dunham, Mentor: Lauren Abrahams , Mentor: Kate Coppess


Earthquakes and volcanoes pose immediate hazards to human society. Our research group develops computer codes to model a wide range of physical processes associated with these hazards. Summer interns have multiple opportunities to apply their computing skills (programming and scripting) and/or the theory of mechanics to explore earthquakes or volcanoes. Students who enjoy programming can assist with code development or running simulations to test a hypothesis; familiarity with unix and prior programming experience in MATLAB, Python, C++, or another language are required. A strong background in calculus-based mechanics is also necessary because we solve solid and fluid mechanics problems (but prior experience with solid and fluid mechanics is not required). Previous experience with earth science is not required.
Spring or Summer

Skills/Interest/Background: Physics, Scientific Programming

Investigating the Impact of Soil Quality on Children's Health and Nutrition in Developing Countries

SESUR, SURGE
Category(s): Food and Agriculture, Human Dimensions and Sustainability
Department: Earth System Science


Soil quality and properties are important factors determining crop health and farm output. These agricultural outcomes are key influencers of household income, food security, and quality of nutritional intake, all of which can determine children's health and growth in low-income countries. Also, specific soil properties, particularly micronutrient content such as zinc and selenium, can directly impact human health and play an essential role in children's development. Current knowledge of the magnitude and extent of soil characteristics' impact in determining children's health outcomes is still limited. We know even less about the potential role of developmental interventions (such as subsidized food, supplemental school meal programs, and others) in mitigating the adverse impacts of low soil quality on children's health. We seek to answer these questions in the proposed study by combining soil test data from India's national Soil Health Card program with remote sensing data on agricultural outcomes and large-scale survey data on children's health and nutrition.

We are looking for a student to assist in data collection, assembly, and analysis, leading to a research report. The specific tasks will include extracting and cleaning the soil tests data from the Soil Health Card program portal, using the cleaned data to create soil health maps for key soil characteristics at varying spatial scales, constructing remote-sensing based measures of crop growth and yield, geospatial matching of soil and yield data with information on children' s health outcome in order to undertake further analysis. Previous experience with (or desire to learn) web-scraping and GIS using R or Python will be helpful. This work can be done remotely.
Spring or Summer

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

Biogeographic patterns of marine animal temperature-dependent hypoxia traits

SESUR
Category(s): Climate Change, Ocean
Department: Geological Sciences
Mentor: Erik Sperling, Mentor: Andy Marquez


THIS PROJECT HAS IDENTIFIED A STUDENT ALREADY.
As oceans warm, marine organisms’ basal metabolic rates rise, increasing their demand for oxygen, while at the same time environmental oxygen supply is limited or decreasing. These synergistic effects of ocean warming and deoxygenation are driving changes in distributions, phenologies, and interactions of marine organisms as they seek environments where their physiological requirements can be maintained. The effects of temperature and oxygen availability on an organism’s aerobic metabolic capacity is captured within a single metric known as the Metabolic Index (
𝚽), with species-specific parameters Ao and Eo representing the overall hypoxia tolerance and temperature sensitivity of hypoxia tolerance respectively. The goal of this project is to compile a database of joint Ao/𝚽crit and Eo values for various marine organisms using biogeographic data to study how temperature-dependent hypoxia traits vary with body size and across latitudinal gradients. We hypothesize that hypoxia tolerance decreases with body size for some organisms (Rhynchonellata and Crinoidea) but not others (Bivalvia, Gastropoda, Cephalopoda) as suggested by fossil record analyses. Additionally, we hypothesize that organisms at the tropics will have lower Ao/𝚽crit values than marine organisms at higher latitudes. Thus, this database will help us to understand which organisms are most vulnerable to temperature-dependent hypoxia and the geographic selectivity of extinction of modern climate change.

We are looking for an undergraduate student to work on this database during the summer as well as potentially travel to the Friday Harbor Labs in the San Juan Islands, WA for two months to help conduct hands-on respirometry experiments. If travel/fieldwork is not allowed by summer 2021, the project can be completed remotely. Previous research experience is not required, but computational skills will be helpful.
Summer only.

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

Using satellites to measure impacts of climate extremes in US agriculture

SESUR, SURGE
Category(s): Climate Change, Food and Agriculture, Human Dimensions and Sustainability
Department: Earth System Science
Mentor: David Lobell, Mentor: Jill Deines


Climate change is expected to increase extreme climate events, including heavy spring rainfalls and summer droughts in agricultural regions. The impacts these events have on crop yields are not well understood but important for agricultural adaptation and food security. The goal of this project is to better understand linkages between climate extremes and crop productivity in the Corn Belt of the US.

The student will use geospatial data derived from satellites to analyze climate impacts at field-level resolution, making this project well suited to both in-person and remote work. Experience with GIS and basic programming skills (python, R, Javascript, etc) and willingness to learn new techniques are helpful. The student will gain knowledge about climate impacts on agriculture and build skills in spatial data analysis and satellite applications in agricultural monitoring.
Spring or Summer.

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

Conservation agriculture: what works and where?

SESUR, SURGE
Category(s): Climate Change, Food and Agriculture, Human Dimensions and Sustainability
Department: Earth System Science
Mentor: David Lobell, Mentor: Jill Deines

Conservation agriculture aims to improve agricultural sustainability by incorporating methods that improve soil health, crop resilience, nutrient management, and carbon sequestration. This movement towards regenerative agriculture is gaining momentum but often lacks quantitative metrics to evaluate the impact across the landscape. These metrics are needed to guide best practices and incentivize action along the food supply chain. This project aims to use satellite-derived data products to evaluate practices such as cover cropping and reduced tillage.

The student will use big data techniques to compare map datasets of management practices, quantify effects on yield and environmental outcomes, and/or fuse data from local studies to support large scale analyses. Experience with GIS and basic programming skills (python, R, etc.) and willingness to learn new techniques are helpful. The student will gain knowledge about conservation agriculture and build skills in data science, causal inference, and agricultural monitoring. This project is computer-based so well suited to both in-person and remote work.
Spring or Summer

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

Fluid migration and thin film stabilization in porous media

SESUR
Category(s): Energy
Department: Energy Resources Engineering

Fluid transport through porous media is important to energy and environmental applications including geological carbon storage, enhanced oil recovery, soil remediation, and energy storage. Multiphase flow and the movement of bubbles of gas dispersed in aqueous fluids are of special interest.  Microscale analysis of the motion and the fluid dynamics of long bubbles provides crucial information to understand the mechanisms of fluid transport and interaction. Factors of interest to understand bubble motion include the length of the bubble, the properties of the gas/liquid interface, pressure drop, and thin film fluid dynamics. Accordingly, this project aims to develop quantitative understanding to explain bubble movement in porous media and seeks to study the effect of additives such as nanoparticles to stabilize the thin liquid films that coat channel walls and surround  bubbles in microchannels.  Our analysis will be microscale and might include experiments using microfluidic devices that permit direct observation of bubble dynamics, computational fluid dynamics calculations, or a combination of experiments and computations. 

This research project ideally involves extensive data collection, processing, and analysis. It also requires fulfilling some basic programming tasks. Students will conduct microscale experiments in the lab, collect the data, and use statistical techniques and image processing to analyze the results and develop significant conclusions from the collected datasets.

We are looking for a researcher with a background in engineering, physics/earth science, statistics and computer science. Strong quantitative skills and experience with programming languages such as Python, C, or MATLAB are advantageous. Students will be mentored closely throughout the entire project, and there will be an opportunity to submit results to a major conference and/or a peer-reviewed journal.

Skills/Interest/Background: Computer Programming, Engineering, Lab Work, Mathematics, Physics, Statistics

Using Psychology, Behavioral Economics, and Linguistics to Study Environmental Attitudes and Behaviors

SESUR
Category(s): Human Dimensions and Sustainability
Department: Emmett Interdisciplinary Program in Environment & Resources
Mentor: Nik Sawe, Mentor: Brian Knutson

We use a combination of methods from behavioral economics, neuroscience, and psychology to study opportunities to improve pro-environmental policy support and behavior change. We have several projects that students can get involved in:

1)     Studying the efficacy of new terminology as replacements for existing terms commonly used in the media related to climate change, renewables, and sustainability, with the aim of finding less partisan, more compelling alternatives. Testing will be in both nation-wide surveys and through interviews and focus groups. Students will assist with survey design in Qualtrics and interviewing of participants, as well as data analysis. Prior experience with interviewing, surveys, NLP techniques, or R is beneficial but not required.

2)     Analyzing the effects of nature imagery in both the US and India, to understand which images are most compelling for eliciting intentions to engage in pro-environmental behaviors, as well as which are the most able to improve mood and other outcomes in individuals who suffer from depression and anxiety, in an effort to study the potential mental health benefits of nature imagery. Students will assist with data analysis. Prior experience with R or other statistical analysis software is required.

Spring or Summer

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

Assessing the determinant traits of extinction and origination selectivity of marine animals with respect to body size

SESUR, SURGE
Category(s): Evolution of Life
Department: Geological Sciences
Mentor: Jon Payne, Mentor: Pedro Monarrez

Animal body size has played an important role in extinction patterns in the fossil record. A widely recognized pattern has been the preferential extinction of larger animals, particularly in terrestrial vertebrates. Recent studies assessing extinction selectivity in marine animal groups, however, suggest that overall, smaller organisms preferentially go extinct during background intervals and mass extinctions. But among some marine classes, larger-bodied animals preferentially go extinct during mass extinctions, suggesting heterogenous responses to mass extinctions among classes. When origination patterns are also assessed, similar patterns result, with selectivity alternating between background intervals and mass extinction recoveries, but not uniformly across classes. Since body size correlates with other organismal traits, such as ecology and physiology, it’s possible that these groups of traits are responsible for the evolutionary dynamics with respect to body size that are observed.

We seek a student to determine which body size correlative traits are more important in determining extinction and origination selectivity for a marine group of animals in the fossil record. The student will assess extinction and origination selectivity among a suite of organismal traits by collecting additional body size data from the published literature and using our existing database. These data will be used in statistical models that estimate extinction and origination probability. Previous experience working with R and statistics will be helpful, but not required. Opportunities to work beyond the summer might also be available. This project is a great opportunity for students seeking to learn about drivers of evolutionary dynamics in the fossil record.
Spring or Summer

Skills/Interest/Background: Scientific Programming, Statistics

Reconstructing Boundary Layer Structure of Tropical Cyclones using Satellite Observations

SESUR, SURGE
Category(s): Natural Hazards
Department: Earth System Science
Mentor: Morgan O'Neill, Mentor: Ipshita Dey

Tropical cyclones are one of the world's most lethal geophysical hazards and their global impact has dramatically increased in the last few decades. Improved forecasting of the most intense tropical cyclone events, especially within the context of climate change has clear implications for future risk assessment and mitigation strategies. Physical processes determining the dynamic and thermodynamic structure of a Tropical Cyclone Boundary Layer (TCBL) are quite different from anywhere else in the atmospheric boundary layer due to the substantial contribution of latent heating and frictional forces. These processes are closely related to storm development and intensification. However, our current understanding of TCBL is limited by the number of observations in this region. Our goal is to characterize the structure of TCBL using advanced microwave-based satellite observations. Microwave remote sensing offer a unique opportunity to observe the atmosphere beneath the cloud base within 1-2km from the surface. We would ideally like to observe, identify and track features unique to TCBL and explain their significance in the intensification of tropical cyclones.

Through this project, the student will develop a good understanding of the observational methods used for retrieving atmospheric variables, statistical tools used for identifying and characterizing the dynamics and thermodynamics of atmosphere as well as assist in the calibration and validation of satellite data. We seek highly motivated students with a mathematical and computational background - preferably with experience in MATLAB/Python/R. Background knowledge in atmospheric physics would be useful but not required.
Summer only.

Skills/Interest/Background: Computer Programming, Mathematics, Physics, Scientific Programming, Statistics

Soil Carbon Protection in Agricultural Soils

SESUR, SURGE
Category(s): Climate Change, Food and Agriculture
Department: Earth System Science
Mentor: Scott Fendorf, Mentor: Emily Lacroix


THIS PROJECT HAS IDENTIFIED A SESUR STUDENT ALREADY.Soils are the largest dynamic reservoir of carbon (C), storing more C than the atmosphere and vegetation combined. Microbial conversion of this C into carbon dioxide (CO2) accounts for ¼ of global CO2 emissions. Recently, anoxic microsites, small zones of oxygen depletion, have been identified as an important soil C protection mechanism, slowing the rate of CO2 production in upland soils. While anoxic microsites likely exert an important control on soil CO2 efflux, surprisingly little is known about the prevalence of anoxic microsites in different types of soil. We want to know whether the contribution of anoxic microsites to soil C protection varies based on soil type and/or management practices. The results of this work should inform land management strategies to maximize soil C storage in cropland soils and ultimately help mitigate global climate change.

As a researcher, you will spend time in analyzing soil samples from various agricultural sites. Potential lab work includes elemental analysis by combustion, density fractionation, soil extractions, texture analyses, and more. This work will help you learn basic laboratory skills as well as how to use and interpret the results of several analytical instruments. There is a small chance for field work, but that is still unknown. We are looking for a student who has strong attention to detail and a willingness to learn. No prior lab experience necessary. If we cannot be in-person, remote work will include literature synthesis and writing, a key skill for any discipline.
Spring or Summer

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

Using quartz to determine the temperature and stress conditions of mylonitization

SURGE
Category(s): Dynamic Earth, Evolution of Earth
Department: Geological Sciences
Mentor: Marty Grove, Mentor: Nikki Seymour


Ductile deformation in the Earth's crust - where rocks flow like taffy rather than breaking suddenly - is recorded by minerals such as quartz. Original quartz grains are deformed and recrystallize into new grains when they are subjected to heat and strain during mountain-building episodes. The size of the new quartz grains and the way they are oriented within the rock record important information about the temperature and stress during the deformation process. This information is particularly important in regions that record multiple episodes of ductile deformation associated with different tectonic events. This project focuses on a polydeformed rock unit: the Orocopia Schist located in the Plomosa Mountains of west-central Arizona.

The student will collect electron backscatter maps of existing rock samples and use grain size and grain orientation analyses to determine the maximum stress and temperatures recorded by quartz in the Orocopia Schist. This information will be integrated with mineral chemistry, microstructural petrography, and geochronology to determine which of two likely tectonic events resulted in the recrystallization of the quartz grains. The student will gain knowledge about operating a scanning electron microscope and build skills in data collection, data analysis through Matlab, and data interpretation. Experience with scanning electron microscopes, basic programming skills (Matlab), and willingness to learn new techniques are helpful but not required. The main requirement is enthusiasm and willingness to try new techniques! This project is partially lab-based (use of the SEM) and partially computer-based (use of MTEX Matlab code) and is suited to a combination of in-person and remote work.

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

Equitable Transportation Decarbonization

SESUR, SURGE
Category(s): Climate Change, Energy, Human Dimensions and Sustainability
Department: Energy Resources Engineering

Equitable Transportation Decarbonization

Mentors: Prof. Margot Gerritsen (ERE), Nora Hennessy (ERE PhD Candidate), and Nadim Saad (CME PhD Candidate)

The transportation sector is responsible for 41% of greenhouse gas emissions in California, and 70% of those come from light-duty passenger vehicles. The Decommissioning Internal Combustion Engine (ICE) Vehicles (DIVE) group studies how to remove conventional gasoline vehicles from the road and replace them with zero emission vehicles (ZEVs). While our main goal is to reduce greenhouse gas emissions, an equally important goal is to promote equity in the transportation sector. In addition to producing greenhouse gas emissions, conventional vehicles emit air pollutants that damage human health, and often disproportionately impact low income and vulnerable communities. Removing conventional vehicles from the road would reduce these damages. On the other hand, vehicles are essential for many people and provide access to work. While the benefits of replacing ICE vehicles with ZEVs are well known, the process will likely be costly, and may place additional burdens on low income families. Our group seeks to understand these dynamics and promote equitable solutions to this challenge.

We are seeking students from all backgrounds who are interested in climate change and issues of environmental justice and equity. Potential projects include analyzing the relationship between transportation emissions, health impacts, and COVID-19; designing equitable policies to remove ICE vehicles from the road without negatively impacting vulnerable communities; or another related project the student is interested in. We will work with the student to develop a specific project to match their skills and interests. All work will be able to be done remotely.
Spring or Summer

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

Risks‌ ‌and‌ ‌opportunities‌ ‌for‌ ‌on-farm‌ ‌recharge‌ ‌to‌ ‌achieve‌ ‌groundwater‌ ‌sustainability‌

SESUR, SURGE
Category(s): Climate Change, Food and Agriculture, Freshwater, Human Dimensions and Sustainability
Department: Emmett Interdisciplinary Program in Environment & Resources
Mentor: Scott Fendorf, Mentor: Randall Holmes


Sustainable management of groundwater resources is critical for achieving global water and food security. California, like many of the world’s groundwater dependent regions, is tasked with addressing declining groundwater levels and climate change’s impacts to the state’s hydrologic system. We use California as a case study for evaluating a promising, distributed solution for restoring groundwater levels in the era of climate change: the flooding of agricultural fields for groundwater recharge, or on-farm recharge. During this project, we will evaluate how the physical science and engineering of balancing groundwater quality and quantity aligns with socio-behavioral challenges, including stakeholder perceptions of risks and opportunities for increasing groundwater storage using on-farm recharge. This research will aid in building an agent-based model, facilitated by Water in the West's Dr. Courtney Hammond-Wagner, to explore the types of incentives, governance structures, monitoring systems, infrastructure, and physical conditions that enable on-farm recharge to support groundwater sustainability. The research will serve as the foundation for piloting an online “On-farm recharge Incentives Dashboard” that will allow water management agencies to explore policies and programs for on-farm recharge in their respective groundwater basins.

Undergraduates working on this project will gain fundamental skills understanding the geochemistry of water quality in California agriculture, as well as coding interviews for content using socio-behavioral constructs, basic data analysis, and insights on how interdisciplinary teams collaborate to incorporate science and engineering research (such as geochemistry and water infrastructure) into policy. We’ll provide the crash course on California water politics! Summer work may lead into opportunities the following academic year. No experience necessary.   

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

Modeling of gasoline particulate filter regeneration in the presence of a catalytic coating

SESUR, SURGE
Category(s): Energy
Department: Energy Resources Engineering


Gasoline Direct-Injection (GDI) engine technology improves vehicle fuel economy toward future targets while, simultaneously decreases CO2 emissions. The main drawback of this technology is the increased emission of particulates (when compared to their indirect injection-based technology counterpart). Thus, aftertreatment devices such as Gasoline Particulate Filters (GPF) are today considered the most promising and practically adoptable solution to limit PM/PN out of GDI exhaust. In a nutshell, the particulate filter traps soot particles resulting from fuel combustion and prevents their release into the atmosphere. Soot oxidation (also known as regeneration) is required at regular intervals to clean the filter, maintaining a consistent soot trapping efficiency, and avoiding the formation of soot plugs in the GPF channel. To enhance the oxidation process, a catalytic coating is usually introduced in the filter.

Starting from a multiphysics model accounting for mass, momentum, and energy transport developed in our laboratory, the candidate should formulate the chemical reactions associated with the regeneration process in case a catalytic coating is present in the filter. Also, relying on experimental data, the identification of the parameters characterizing the reaction kinetics should be performed with the help of non-linear optimization tools. Knowledge of Matlab&Simulink and of COMSOL Multiphysics (or similar) is required for the model implementation and simulation activities.

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

Exergy-based modeling of a fuel cell hybrid electric vehicle

SESUR, SURGE
Category(s): Energy
Department: Energy Resources Engineering


In the last years, the quest for energy efficiency has led the research community to devote time and effort towards the development of new powertrain solutions for the next generation of vehicles. In this context, to evolve the standard internal combustion engine technology, hybrid electric vehicles are of interest. As a matter of fact, the introduction of multiple power sources allows for the improvement of the fuel economy and for the reduction of pollutants emissions. To benefit from hybrid architectures it is of paramount importance to introduce effective management strategies, which allow for the optimization and balancing of the power sources. In this context, the modeling of the powertrain irreversibilities relying on the second law of thermodynamics (or, in other words, on exergy and entropy) is gaining interest. This particular approach allows to explicitly formulate the loss terms for all the powertrain constituents (transmission, battery, electric motor, internal combustion engine, etc.). This allows to understand the major source of inefficiency and also to develop optimization strategies to minimize these losses.

The ideal candidate should be passionate and interested in the thermodynamics modeling of systems. The project will allow to learn fundamental concepts in the context of the second law of thermodynamics analysis of systems. In particular, the candidate will develop and simulate an exergy-based model for fuel cells, to be introduced in the hybrid vehicle modeling framework we have developed in our laboratory. Knowledge of Matlab&Simulink is required for the model implementation and simulation activities.

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

Exploring the interaction of wind-driven internal waves with the Florida Current

SURGE
Category(s): Dynamic Earth, Ocean
Department: Earth System Science
Mentor: Leif Thomas, Mentor: Lixin Qu


Winds blowing over the ocean generate waves, not just the familiar ones that ride along the surface, but another type which travel down into the deep sea. These so-called internal waves can transmit a large amount of wind energy downwards and thus are thought to play an important role in sustaining the deep branch of the ocean circulation and in driving mixing. This study will explore the physics of wind-driven internal waves in the Strait of Florida where preliminary calculations suggest that the interaction of the waves with the strong Florida Current is quite effective at enhancing downward energy transport and mixing. The project will involve running and analyzing high-resolution numerical simulations to understand the underlying dynamics of this interaction more fully and to assess its impacts on the mixing and transport of biogeochemical tracers.

We seek a motivated student interested in using scientific programming (in particular Python and Fortran) to study the physics of the ocean. While experience in oceanography is not required, a background in math and/or physics, and programming is necessary.

Skills/Interest/Background: Mathematics, Physics, Scientific Programming
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