Rural areas, which contain approximately 20% of the US population and over 90% of the land area in the United States, are fundamental to human well-being in both rural and urban areas. Rural areas provide resources such as the infrastructure for U.S. food and bioenergy production as well as the transportation infrastructure from inland urban centers to ports. Rural areas are characterized by agricultural- and natural resource-based economics, stable or declining populations with low population densities, and “farm-to-market” localized transportation patterns, and these characteristics necessitate new technologies and approaches for civil infrastructure. Despite the differences between rural and urban regions, little attention is paid to the unique challenges and opportunities for sustainability in rural areas.
In this ten-week summer research program, students will work with faculty in the Department of Civil Engineering to conduct research and will contribute new knowledge to improve our understanding of how best to address the challenges facing rural environments. Through collaboration with industry partners, students will also be given opportunities to learn how infrastructure challenges are currently being addressed by the civil engineering industry. In addition, this program offers a series of communication development opportunities including preparation of a conference paper, informal presentations to their peers, formal poster presentations, and outreach to high school students.
Competitive stipend: $5,000
Suite-style room and meal plan
Travel expenses to and from Lincoln
Campus parking and/or bus pass
Full access to the Campus Recreation Center and campus library system
Significance: The occurrence of microplastics, an emerging contaminant in agricultural systems, is very poorly characterized. Plastics are a frequently observed component of marine debris and there is growing concern about microplastic ecotoxicity, and the impacts of sorbed hazardous organic contaminants, heavy metals and biofilms on microplastic surfaces. However, microplastics are increasingly being found in terrestrial freshwater environments in addition to marine systems. In wastewater treatment plants, microplastics are often associated with biosolids, which are typically applied to cropland as a fertilizer. To date, there is little information about the transport of microplastics from fields with land applied biosolids to freshwater or infiltration into agricultural soil. The primary research questions to be addressed in this project: (1) are microplastics transported in runoff from fields with land applied biosolids? and (2) are there specific microplastic morphologies (shapes) that are most commonly transported?
Student Participation: The REU student will collect runoff samples from test plots with land applied biosolids and control plots (containing no biosolids) established at Rogers Memorial Farm, a no-till research farm at UNL. The student will separate and characterize the microplastics using microscopy. Student Outcomes: The REU student will gain exposure to field research in an on-farm setting and laboratory training in microplastic characterization methods including elutriation, density separation and oxidation. The student will learn to use visible light and UV microscopes. Prerequisite Knowledge and Training: No formal course prerequisites. Microscopy training to be conducted during the first week of the program by the graduate student and faculty mentor.
Characterization of Gas Production and Mechanical Properties of Solid Waste in Rural Areas
Significance: Landfills are typically sited in rural areas with low population densities. Gas production and leachate can be particularly concerning in rural areas due to the reliance upon groundwater. Therefore, accurate predictions of landfill gas (LFG) emissions and waste settlement are crucial for the prevention of greenhouse gas emissions and for sustainable management of a municipal solid waste (MSW) landfill. The objective of this research is to characterize gas production and leachate of solid waste by using a direct injection logger including a piezocone penetration test (PCPT) with a hydraulic profiling tool (HPT) and membrane interface probe (MIP). This project aims to evaluate the properties of landfills and determine best practices for sustainable management of gas production. The primary research questions to be answered in this project are: 1) Can gas production be accurately measured in landfills using an in situ method? and 2) What are the in situ mechanical properties of solid waste?
Student Participation: As part of this project, the student participant will collect soil properties and gas emission data using PCPT with MIP and HPT from an operating landfill in Butler County, Nebraska, a rural county with a population of 8,000. Student Outcomes: The student will learn how to survey soils and measure gas emission using state-of-the-art technologies and conduct statistical analysis of data. Prerequisite Knowledge and Training: No formal prerequisites, training on using the measurement equipment will be provided by the faculty mentor and graduate student mentor during the first two weeks.
Dr. Xu Li
Civil and Environmental Engineering: Environmental Engineering
Limiting the transport of antimicrobials and antimicrobial resistance genes in the environment
Significance: The extensive use of antimicrobials (AMs) in the livestock industry for animal disease treatment/prevention and growth promotion has promoted the emergence of antimicrobial resistant bacteria. Antimicrobial resistance genes (AMR genes) - the genetic materials that render resistance mechanisms to bacteria - can proliferate among the bacteria in the environment. If human pathogens acquire AMR genes and become antimicrobial resistant, antibiotic treatment will lose its effectiveness in treating infected individuals. The goal of this research project is to understand the fate and transport of AMs and AMR genes in the agricultural environment and develop best management practices (BMPs) to control their proliferation.
Student Participation: The REU student will collect samples from pilot-scale reactors and analyze them for their effectiveness in removing AMs and AMR genes. Student Outcomes: Through this project, the student will learn how to use advanced analytical and molecular techniques to measure AMs and AMR genes in environmental samples. The student will also discover how different management practices may influence the fate and transport of AMs and AMR genes in the environment. Prerequisite Knowledge and Training: College chemistry, which is typically covered in the first year of most undergraduate programs. Analytical and molecular techniques will be trained over the first two weeks of the program by the faculty mentor and graduate student mentor.
Dr. Yusong Li
Civil and Environmental Engineering: Water Resources Engineering
Evaluating and Predicting Agricultural Nonpoint Source Pollution under a Changing Climate
Significance: Agricultural nonpoint source pollution (NPS) is a significant contributor to the contamination of surface water and groundwater resources. With increasing demands on global agricultural production and the need to maintain sustainable water resources in the future, it is crucial to identify areas with high agricultural NPS potentials. Understanding the spatial distribution of NPS pollution is essential for the design of mitigation strategies. This project will quantify and predict the spatial distribution of agricultural NPS risks in the United States under historical and future climate scenarios. A transformed agricultural nonpoint pollution potential index (T-APPI) will be calculated to quantify the NPS risks.
Student Participation: The REU student will develop Geographic Information System (GIS) maps of contaminant concentration distribution in Nebraska. The student will use such maps to evaluate the accuracy of the T-APPI estimation for NPS risk distribution. Student Outcomes: Student will learn to use advanced (GIS) mapping technology. The student will also learn to research commonly used Federal and State database to obtain water quality data. Prerequisite Knowledge and Training: No formal course prerequisites. The student will be trained to use GIS software in the first week of the program by the graduate student mentor.
Smart Big Data Pipeline for Aging Rural Transportation Infrastructure
Significance: While transportation infrastructure around the nation is in poor health, rural areas are acutely affected by this crisis due to their low population density and distance from urban centers. More specifically, Nebraska has the 7th highest percentage of structurally deficient rural bridges in the U.S. With 60% of those bridges constructed between the 1930s and 1960s, the aging infrastructure must receive periodic inspections to assess potential deficiencies. This project strives to develop a reference smart big data pipeline for aging rural bridges, which are important components of our rural transportation network. The project combines existing and new datasets to address challenges of relevance to bridge owners using scalable and replicable big data pipeline components. Activities will inform bridge owner decision-making by integrating existing datasets and data collected using next-generation health monitoring technologies (e.g., contact and non-contact sensors, unmanned aerial vehicles) with innovative data management. The primary research questions to be addressed in this project are: 1) How can legacy and advanced sensing techniques be integrated into a structural health monitoring system in a fashion that increases its effectiveness? and 2) Can simplified models provide robust information that facilitates examining the effects of decisions on future bridge health and service life?
Student Participation: The student will conduct field testing of rural bridges and reduce/examine collected field data in support of advanced filtering and neural network techniques for structural health monitoring systems. Student Outcomes: Student will gain an understanding of bridge structures, instrumentation, field testing, and data manipulation techniques. Prerequisite Knowledge and Training: Field testing, instrumentation and data reduction and manipulation training will be conducted by a graduate or post-doctoral student mentor.
Effectiveness of Floating Treatment Wetlands for Pesticide and Nutrient Removal
Significance:Nitrate-N contamination is persistent in rivers and groundwater throughout the world and a major cause for drinking water impairment across the United States. Floating treatment wetlands (FTWs) are now used extensively across the United States as a means for mitigating nitrate-N losses to both surface and groundwater due to their cost effectiveness and low energy consumption. While the use of wetlands as a treatment approach for nitrate-N is well known, nitrate-N is not the sole constituent in runoff from agricultural fields. Common use pesticides (CUPs) and antibiotics, while important for agricultural productivity, have become ubiquitous in waterways worldwide resulting in significant effects within agroecosystem food webs and human health. The primary research objective is to identify the physical and biogeochemical water quality parameters that enhance CUP and antibiotic removal using FTWs.
Student Participation: The REU student will conduct experiments to assess the impact of three wetland designs on CUP and antibiotic removal. Water quality parameters will be evaluated throughout the experiments using in-situ sensors, grab water quality samples, and plant samples. Student Outcomes: The student will gain an understanding of the impacts CUPs have on biological treatment systems and the surrounding ecology in order to provide design recommendations to limit ecosystem disturbances. Prerequisite Knowledge and Training: College chemistry, which is typically taken in the first year of college programs. Training on experimental protocols and water quality collection and analysis will be conducted by the faculty mentor.
Computer-Vision Based Health Monitoring of Aging Rural Bridge Infrastructure
Significance: The number of aging rural bridges are increasing in Nebraska. When it comes to make decisions to repair, rebuild, or rehabilitate these aging rural bridges, decisions are made by prioritizing the ranks of these bridges. Condition ratings made by the inspectors for bridge deck, superstructure, and substructure are one of the parameters used in this decision making. Human visual inspection is typically conducted first and if needed, additional measures are used to assess the level of deterioration for condition ratings. This process becomes a challenge when there are thousands of bridges and limited number of inspectors available. To assist this inspection process, this project will focus on developing a computer-vision based system to monitor the health of our aging rural bridge infrastructures.
Student Participation: The REU student will assist with collecting data, labeling images, detecting features using state-of-the art machine learning and deep learning algorithms, and creating a quantitative database for tracking temporal and spatial changes to monitor the progression of damage deterioration. Student Outcomes: The student will gain an understanding of machine learning and computer vision. Prerequisite Knowledge and Training: No formal coursework necessary.
Significance: Rural bridges are crucial to agricultural economic activities, particularly during harvest seasons when crop yield transportation imposes heavy loads on bridges. Many bridges in rural areas are at or beyond their intended service life and were designed either for unknown or lower vehicle loading than required in modern codes. Unnecessarily imposing load restrictions on bridges leads to increased trip frequencies and lengths for freight vehicles, or demolishing and replacing safe bridges. Therefore, it is desirable to maximize permitted vehicle loading and extend service lives of aging bridges. Reassessing the structural capacity and mechanical response to vehicular loads for rural bridges is critical to achieving this goal. The primary research question that this project addresses is: how does uncertainty in mechanical response to vehicular loads influence structural reliability for rural bridges?
Student Participation: The REU student on this project will conduct analyses to investigate the relationships between uncertain structural characteristics (e.g. composite shear transfer on steel beams designed neglecting composite action) and risk-targeted safe load carrying capacity. The student will propose, conduct, and analyze results for a small experimental testing plan related to the analytical work. Student Outcomes: The student will gain experience performing structural experimental testing and an understanding of 3-dimensional structural system behavior. The student will be introduced to probabilistic concepts for structural engineering evaluation and reliability assessment, advanced mechanical modeling, and machine learning techniques. Prerequisite Knowledge and Training: Mechanics, which is typically acquired by the second year in an engineering program.
Resilience of Agricultural Infrastructure and Rural Communities to Natural Hazards
Significance: Despite the criticality of the agricultural industry to both U.S. and global sustainable food production, the resulting lack of economic diversity in most rural areas is theorized to be a major contributor to the low resilience of rural communities to natural hazards, including earthquakes and windstorms. While resilience is a function of many socioeconomic and organizational factors, the disaster response of the built environment is a critical aspect that cannot be ignored. In many rural areas, critical infrastructure includes vital agricultural support and production systems, such as irrigation systems, storage silos, and low-rise hoop buildings. However, many of these systems do not conform to typical engineering design and analysis methods, and have been observed to perform poorly during past earthquakes and severe windstorms. This research aims to generate a fundamental understanding of the performance of agricultural infrastructure to extreme loads in an effort to enhance rural resilience to natural hazards.
Student Participation: The student will conduct scaled (tabletop) shake table tests of storage silo structures in support of a parametric study evaluating the rate of uplift and overturning. The student will have the autonomy to expand the test matrix as they interpret the results. Student Outcomes: Student will gain basic understanding of natural hazards, agricultural infrastructure, and experimental design which are typically not covered in undergraduate courses. Prerequisite Knowledge and Training: College-level mechanics/physics, which is typically covered during the first year. Shake table training will be conducted by the faculty mentor during the first week of the program.
Monitoring and Evaluation of Low-Volume Rural Roadways
Significance: Given the criticality of transportation infrastructure to the agricultural industry in many rural areas, routine evaluation of roadway condition is imperative such that appropriate maintenance can be undertaken, and unnecessary closures avoided. Due to the low-volume use of many rural and gravel roadways combined with the potential remote location, condition assessment is a time-intensive and expensive task that is oftentimes neglected. Point clouds representative of the road surface can be used to robustly and accurately measure the change to roadways; however, a number of challenges arise for implementation and analysis in remote areas and over long distances. This project addresses two of these key challenges as stated in the following research questions: 1) What geometric properties of roadway surfaces are indicative of damage and deterioration? and 2) How can ground control and GPS be efficiently utilized in remote areas and over long distances to accurately constrain point clouds?
Student Participation: In the first year of this project, the student will conduct a series of field investigations with various ground control points (or benchmarks) and examine the distribution of error, both locally and globally. The student will process and analyze the experimental data to identify effective strategies for efficient data collection. Student Outcomes: The student will gain an understanding of point clouds and geospatial data as applied for civil engineering, as well as experience collecting this data, which is typically not taught in undergraduate courses. Prerequisite Knowledge and Training: No formal coursework necessary. Data collection procedures will be trained by a graduate student mentor during the first week.