Exploring a shallow landsliding event with a multidimensional stability model
Shallow landslides are a primary method of sediment transport and a dominant hillslope erosion process in many steep, soil-mantled landscapes. However, testing models that predict shallow landslide size and location is challenging due to a lack of high resolution datasets that map where landslides occurred following major storms. In February 2017, an intense rainfall event caused more than 400 shallow landslides at a field research site near Williams, California. This project will use a comprehensive landslide dataset that I created from field surveys over the past year to statistically analyze how successful a newly published model and search algorithm by Milledge et al. (2014) and Bellugi et al. (2015) are at predicting the size and location of landslides that occurred at this site. Testing this model is essential for determining when the model is predictive and under what conditions the model fails, ultimately furthering our theoretical understanding of the processes that cause shallow landsliding.
Message to Sponsor
- Major: geophysics
- Sponsor: Rose Hills Independent
- Mentor: Bill Dietrich