Enhancing Regional Landslide Susceptibility Models through Basin History-Based Framework for Rock Strength Estimation
Abstract
Earthquake-triggered landslides pose a significant hazard in many regions of California where large population centers are developed on geologically young and fragile rock masses near active fault systems. Conventional landslide susceptibility models utilize Mohr-Coulomb strength parameters to assess slope stability under earthquake-induced loading, but these inputs are often crudely estimated based on map unit lithology alone. Previous work in the Western Transverse Ranges (WTR) in southern California has demonstrated a high degree of variability in field-based rock mass properties in geologically young rocks of identical lithology, indicating that rock type alone is not sufficient for accurate estimates of landslide susceptibility. To address shortcomings in lithology-based estimates, we propose a multiscale assessment framework for rock mass strength proxies that incorporate basin depositional and exhumation history. We leverage an extensive dataset of field-based strength measurements (geologic strength index (GSI), and uniaxial compressive strength (UCS)), 2D shallow geophysical surveys (multichannel analysis of surface waves (MASW), electrical resistivity imaging (ERI), and electromagnetic (EM) methods), thin section analysis, and laboratory strength tests to characterize changes in rock properties. Rock mass properties are further related to burial history of an inverted sedimentary basin along a mountain transect where exhumation rates are uniform. As an outcome of this work, improved subsurface characterization and strength parameters are assigned across the WTR and utilized in regional landslide numerical simulations based on scenario ruptures on the Ventura fault system. Due to the prominence of young clastic rocks along the coastal mountain ranges of California, this framework may be extended beyond the WTR in the future to similar geologic and tectonic settings throughout California.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2023
- Bibcode:
- 2023AGUFM.S43G0422K