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Landslide Sensitivity and Response to Precipitation Changes in Wet and Dry Climates.

Alexander L HandwergerEric Jameson FieldingSimran S SanghaDavid P S Bekaert
Published in: Geophysical research letters (2022)
Slow-moving landslides are hydrologically driven. Yet, landslide sensitivity to precipitation, and in particular, precipitation extremes, is difficult to constrain because landslides occur under diverse hydroclimatological conditions. Here we use standardized open-access satellite radar interferometry data to quantify the sensitivity of 38 landslides to both a record drought and extreme rainfall that occurred in California between 2015 and 2020. These landslides are hosted in similar rock types, but span more than ∼2 m/yr in mean annual rainfall. Despite the large differences in hydroclimate, we found these landslides exhibited surprisingly similar behaviors and hydrologic sensitivity, which was characterized by faster (slower) than average velocities during wetter (drier) than average years, once the impact of the drought diminished. Our findings may be representative of future landslide behaviors in California where precipitation extremes are predicted to become more frequent with climate change.
Keyphrases
  • climate change
  • heat stress
  • electronic health record
  • current status
  • cross sectional
  • machine learning
  • risk assessment
  • deep learning