GEO-LEOedocs LogoGEO-LEOedocs Logo
  • GEO-LEO
    • Deutsch
    • English
  • GEO-LEO
  • English 
    • Deutsch
    • English
  • Login
View Item 
  •   Home
  • Alle Publikationen
  • Geologie
  • View Item
  •   Home
  • Alle Publikationen
  • Geologie
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Seasonal Landslide Activity Lags Annual Precipitation Pattern in the Pacific Northwest

Luna, L. V.ORCIDiD
Korup, O.ORCIDiD
DOI: https://doi.org/10.1029/2022GL098506
Persistent URL: http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/10430
Supplement: https://data.nasa.gov/Earth-Science/Global-Landslide-Catalog/h9d8-neg4
Luna, L. V.; Korup, O., 2022: Seasonal Landslide Activity Lags Annual Precipitation Pattern in the Pacific Northwest. In: Geophysical Research Letters, Band 49, 18, DOI: 10.1029/2022GL098506.
 
Thumbnail
View/Open
GRL_GRL64881.pdf (1.148Mb)
Metadata Export:
Endnote
BibTex
RIS
  • Abstract
Seasonal variations in landslide activity remain understudied compared to recent advances in landslide early warning at hourly to daily timescales. Here, we learn the seasonal pattern of monthly landslide activity in the Pacific Northwest from five heterogeneous landslide inventories with differing spatial and temporal coverage and reporting protocols combined in a Bayesian multi‐level model. We find that landslide activity is distinctly seasonal, with credible increases in landslide intensity, inter‐annual variability, and probability marking the onset of the landslide season in November. Peaks in landslide probability in January and intensity in February lag the annual peak in mean monthly precipitation and landslide activity is more variable in winter than in summer, when landslides are rare. For a given monthly rainfall, landslide intensity at the season peak in February is up to 10 times higher than at the onset in November, underlining the importance of antecedent seasonal hillslope conditions.
 
Plain Language Summary: Better knowing when landslides are likely over the course of the year can reduce landslide risk by improving emergency preparedness. One research challenge is that catalogs of past landslides rarely cover the same areas or time periods, and have been collected in different ways. Here, we use statistical models to estimate monthly landslide activity in the Pacific Northwest. The models are able to combine five different landslide catalogs to make best use of all available information. We find a seasonal pattern in both the average number of landslides in a month and the probability of having any landslides. The landslide season begins in November, when the average number and the probability of landslides increase. The probability of landslides peaks in January and the average number in February, lagging behind winter rainfall peaks by one to two months. While landslides are least likely in summer, their activity is more variable in winter, with some winters bringing hundreds of landslides, and some very few. At the landslide season peak in February, a comparable amount of rain leads to many more landslides than at the onset in November, likely because already wet hillslopes are more prone to failure.
 
Key Points: Bayesian inference learns the seasonal pattern of landslide activity in the Pacific Northwest from five combined heterogeneous inventories. Landsliding is distinctly seasonal with highest probability (intensity) in January (February), lagging the annual precipitation peak. Landslide intensity for a given monthly rainfall during peak season in February is up to 10 times higher than at the onset in November.
Statistik:
View Statistics
Collection
  • Geologie [755]
Subjects:
landslide
seasonality
Pacific Northwest
Bayesian multi‐level models
logistic regression
negative binomial regression
This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

ImpressumPrivacy (Opt-Out)Cookie ConsentsAbout us/ContactDeposit LicenseSubmission hintsSupport: fid-geo-digi@sub.uni-goettingen.de
DFGSUBFID GEOFID Montan
 

 

Submit here
Submission hints
Search hints

All of Geo-Leo e-docsCommunities & CollectionsBy Issue DateContributorsSubjectsPeriodicalsTitlesThis CollectionBy Issue DateContributorsSubjectsPeriodicalsTitles

Statistics

View Usage Statistics

ImpressumPrivacy (Opt-Out)Cookie ConsentsAbout us/ContactDeposit LicenseSubmission hintsSupport: fid-geo-digi@sub.uni-goettingen.de
DFGSUBFID GEOFID Montan