T177 Current Trends in Landslide Inventories and Assessments: Innovative Techniques, Collection Methods, Modeling, and Risk (Posters)

Tuesday, 24 September 2024
8:00 AM - 5:30 PM
Hall D

PATTERNS AND DRIVERS OF CLIFF EROSION IN BIG SUR USING REPEAT PHOTOGRAMMETRY, 2017-2023

Paper number: T177-10
Program: Technical Sessions
Time: 8:00 AM – 5:30 PM

Authors

  • Helen W. Dow Presenting Author
    Pacific Coastal and Marine Science Center, Santa Cruz, CA
  • Jonathan A. Warrick
    Pacific Coastal and Marine Science Center, Santa Cruz, CA
  • Amy E. East
    Pacific Coastal and Marine Science Center, Santa Cruz, CA
  • Joel B. Sankey
    Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, Flagstaff, AZ

Abstract

Big Sur is characterized by its rocky coastline with high coastal cliffs and steep coastal slopes. Cliff erosion and fluvial sediment flux from small, high-relief catchments supply sediment to littoral cells and replenish the few small pocket beaches that line this coastline. Cliff erosion also threatens the sustainability of the Big Sur stretch of California State Highway 1, a scenic roadway that is important to the region’s transportation and tourism. Long-term (~70 year) cliff retreat rates are on the order of ~0.3 ± 0.2 m a-1, which results in ~ 20,000 m3 km-1 a-1 of cliff erosion (Hapke, 2005; Hapke et al., 2009), but the patterns and drivers of cliff erosion in the region remain unconstrained over shorter timescales and at individual locations. We focused on a ~12 km of coastline from McWay Falls to Gorda Point, because this region is north of the larger deep-seated landslides in the region, allowing us to focus exclusively on cliff erosion. We used oblique aerial imagery from 33 single-pass flights taken between January 2017 and June 2023 to construct point cloud models of the cliff face (one for each flight) using four-dimensional structure-from-motion (4D SfM) photogrammetry techniques. Notably, three of these years (2017, 2019, and 2023) were above-average water years with numerous atmospheric rivers bringing high-intensity rainfall and large waves to the region. We used point-cloud change-detection techniques to calculate cliff face change between each of the 33 flights. With this dataset, we seek to quantify the magnitude of erosion over each time step, identify primary mechanisms of cliff erosion (e.g., shallow landslides, rill erosion) in our study area, and investigate the drivers of spatial and temporal variability in cliff erosion, such as bedrock lithology and precipitation depth and intensity.

Hapke, C.J., 2005. Estimation of regional material yield from coastal landslides based on historical digital terrain modelling. Earth Surface Processes and Landforms 30, 679–697. https://doi.org/10.1002/esp.1168

Hapke, C.J., Reid, D., Richmond, B., 2009. Rates and Trends of Coastal Change in California and the Regional Behavior of the Beach and Cliff System. Journal of Coastal Research 25, 603–615. https://doi.org/10.2112/08-1006.1

Geological Society of America Abstracts with Programs. Vol. 56, No. 5

doi: 10.1130/abs/2024AM-404405

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