2026-07-09 カリフォルニア大学サンディエゴ校（UCSD）
Before and after oblique images of the landslide with red triangles representing the locations of MEMS tilt sensors. Image credit: Scripps Institution of Oceanography
＜関連情報＞
- https://today.ucsd.edu/story/new-report-outlines-potential-to-predict-coastal-cliff-collapses
- https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025JF008562
カリフォルニア州サンディエゴ郡における海岸崖崩れのリアルタイム地盤変形記録 Real-Time Ground Deformation Records of Coastal Cliff Failures in San Diego County, California
Matthew J. Cook, Adam P. Young, Frank K. Wyatt, Mark A. Zumberge
Journal of Geophysical Research: Earth Surface Published: 07 April 2026
DOI:https://doi.org/10.1029/2025JF008562
Abstract
Coastal cliff failures pose significant risks to public safety and coastal infrastructure, especially in southern California. We deployed a suite of continuous geophysical sensors to investigate failure processes and precursory behaviors at three coastal clifftop sites in San Diego County: San Elijo State Beach and two locations in Del Mar. Our sensors captured baseline and pre-failure signals, and cliff collapses, revealing patterns in ground deformation leading up to failure. Across all sites, we observed stages of accelerating ground displacement corresponding to the creep stage of imminent failure. Inconsistent best-fit functions highlight the complexity of cliff failure dynamics while velocity and acceleration relationships and inverse velocity provide more reliable indicators of imminent collapse, aligning with established slope failure models. Cliff failures often occur following storms, highlighting the influence of environmental factors, particularly rainfall, on erosion, instability, and failure. These findings demonstrate the benefits of continuous geophysical monitoring for characterizing cliff instability in near real-time and provide valuable insights for hazard mitigation and early warning applications.
