Collaborative Research: Reading lithology from topography: How rock properties influence landscape form and evolution in the Guadalupe Mountains, TX and NM

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The shape of landscapes partly depends on the physical properties of the bedrock that underlies them (e.g., how strong different rock types are in different places, how fractured the rocks are, and how easily particular rocks break down to make soil and sediment, also known as weathering). It should be possible to "read" rock properties from landscape form (topography), but we currently lack a quantitative relationship that can be used practically. For example, the likelihood of landslides depends on rock and soil properties. Past tectonic activity and the potential for future earthquakes along faults can also potentially be inferred from topography, but the effects of tectonics must be isolated from rock property controls on landscape form. Predicting land surface properties would also be beneficial for planning access to remote areas following natural disasters or during human conflicts. The researchers will develop teaching modules based on the Guadalupe Mountains to use in a dual enrollment (i.e., college credit for high school students) geoscience course taught through UT Austin that provides college credit to high school students across Texas. High school geoscience and environmental science teachers will be trained through intensive and fun field workshops to be taught in the Guadalupe Mountains.This project uses the Guadalupe Mountains in Texas and New Mexico as a natural laboratory to understand how rock properties can be inferred from topography. In addition to (a) using geographic information system analysis to relate meter-scale topographic data and digital geology maps, the researchers will also (b) make extensive field measurements of rock properties across this landscape, (c) determine long-term bedrock erosion rates by measuring cosmogenic radionuclide concentrations from rock samples, and (d) evaluate open-source computer models that predict how landscapes will evolve through time, and improve these models to better incorporate rock properties into their equations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.