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Seasonal landslide activity lags annual precipitation pattern in the Pacific Northwest

  • 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.

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Metadaten
Author details:Lisa LunaORCiDGND, Oliver KorupORCiDGND
DOI:https://doi.org/10.1029/2022GL098506
ISSN:0094-8276
ISSN:1944-8007
Title of parent work (English):Geophysical research letters
Publisher:Wiley
Place of publishing:Hoboken, NJ
Publication type:Article
Language:English
Date of first publication:2022/09/28
Publication year:2022
Release date:2024/08/16
Tag:Bayesian multi-level models; Pacific Northwest; landslide; logistic regression; negative binomial regression; seasonality
Volume:49
Issue:18
Article number:e2022GL098506
Number of pages:11
Funding institution:DFG RTG "Natural Hazards and Risks in a Changing World"; Projekt DEAL
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Umweltwissenschaften und Geographie
DDC classification:5 Naturwissenschaften und Mathematik / 50 Naturwissenschaften / 500 Naturwissenschaften und Mathematik
Peer review:Referiert
License (German):License LogoCC-BY-NC - Namensnennung, nicht kommerziell 4.0 International
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