Combining outcrop, magnetic, and airborne LiDAR data in a course-based undergraduate research experience (CURE): interpretation of bedrock fracturing in the northeastern Deep River Basin and adjacent basement, North Carolina
Abstract
Course-based undergraduate research experiences (CUREs) are a way for students to learn the power of combining geological, geophysical, and geodetic datasets, while also generating new results to answer real questions. A 5-week undergraduate geophysics CURE combined newly released public domain LiDAR-derived ground models with outcrop and magnetic data. The goal was to see if this approach could improve understanding of bedrock fracture sets in the NC Piedmont, which in turn would improve decisions about groundwater resources and proposed hydraulic fracturing of "tight" shale reservoirs in the 230 Ma Deep River failed rift basin. The 10 km2 study area was selected because it straddles the fault contact between crystalline basement and basin sedimentary rocks, it contains 200 Ma NW-SE trending mafic dikes related to successful rifting of Pangea common in the Piedmont, bedrock exposure is typical of the Piedmont (poor), and its land use history is representative of much of the Piedmont. Students visited representative field sites to collect observations then manually identified lineaments in several adjacent LiDAR ground model tiles. Results suggest that (1) lineaments as short as a few m are easily identified except underneath Quaternary deposits, (2) the dominant lineament set trends NW-SE with m- to 10 m-scale spacing, (3) lineaments are better expressed in sedimentary rocks and (4) do not spatially coincide with dike traces. Using field observations, map patterns, and total magnetic intensity profiles across several dikes, the lineaments are interpreted to be edges of subvertical joint fractures recording extension parallel to the dikes' dilation direction. The CURE concluded with students in small groups proposing next steps for the larger research project. The CURE introduced geology majors to the power of using geophysical and remote sensing data with geological data to address geoscience questions. Student feedback was very positive even though the learning curve with software and dataset interpretation was steep. Two students opted to continue independent work on the project (one for a senior thesis), suggesting that the earlier students work with multi-disciplinary datasets, the more likely they will consider these approaches in their research and professional development.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMED11B0130P
- Keywords:
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- 0810 Post-secondary education;
- EDUCATION;
- 0820 Curriculum and laboratory design;
- EDUCATION;
- 0825 Teaching methods;
- EDUCATION