Quantifying the connection between rock material properties and the topography of mountain ranges is critical for understanding how climate and tectonics influence landscapes and for predicting natural hazards. However, incorporating rock strength into landscape evolution models has been a challenging problem. This is due in part to difficulties in defining appropriate metrics to describe rock strength, and because the factors that determine rock strength vary in importance depending on erosion process. This project aims to address this knowledge gap by testing the hypothesis that in steep landscapes, rock strength exerts a first order control on landscape-scale erodibility through the influence of fracture density on bedrock hillslopes and the resulting grain size distribution of sediment delivered to channels.
By comparing topographic metrics of hillslope and channel relief with erosion rates determined from cosmogenic nuclide concentrations in stream sediment, this project will characterize differences in erodibility between two landscapes in Southern California with similar topography, rock type, and climate, but strongly contrasting tectonic history and bedrock fracture density. This project will take advantage of new ground-based photogrammetry techniques and analysis of high-resolution airborne lidar data to upscale field observations and measurements to entire landscapes. Development and testing of novel point-cloud and image-based analysis techniques will provide training and experience for geoscience undergraduates through classroom laboratory exercises and independent research projects. Results from this project will provide a framework for making progress on the challenging task of expanding site-specific correlations between relief and erosion rate to regions with differing rock strength and climate, and inform provocative hypotheses regarding potential feedbacks between tectonic setting and bedrock fracturing that limit the height of mountain ranges.
|Effective start/end date
|6/1/16 → 5/31/21
- National Science Foundation: $315,052.00