Granular Scaling Approach to Landslide Runout
Rory T Cerbus1,2, Ludovic Brivady2, Thierry Faug3
1RIKEN Center for Biosystems Dynamics Research (BDR), 2-2-3 Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan.
Predicting landslide runout distance is crucial. This study simplifies prediction by linking fall height and grain size distribution to landslide mobility, uniting lab and field data.
Area of Science:
- Geosciences
- Geotechnical Engineering
- Natural Hazards
Background:
- Landslide research aims to predict travel distance, a complex phenomenon.
- Numerous parameters influence landslide behavior, complicating accurate predictions.
Purpose of the Study:
- To simplify landslide runout prediction.
- To investigate the relationship between fall height, grain size distribution, and landslide mobility.
Main Methods:
- Granular laboratory experiments were conducted.
- A scaling analysis was performed on experimental and field data.
Main Results:
- Accounting for fall height and grain size distribution improved normalized runout correlation.
- Laboratory and field data were quantitatively unified.
- Landslide mobility increases with the square root of fall height.
- Landslide mobility increases with the skewness of the grain size distribution.
Conclusions:
- Fall height and grain size distribution are key parameters for predicting landslide runout.
- The developed model provides a unified approach for laboratory and field landslide data.
- The findings offer a simplified yet effective method for landslide mobility assessment.
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