Controls on the grain size distribution of landslides in Taiwan: the influence of drop height, scar depth and bedrock strength
Bibliographic record
Abstract
The size of grains delivered to rivers by hillslopes processes is thought to be a key factor to better understand sediment transport, long-term erosion as well as sedimentary archives. Recently, models have been developed for the grain size distribution produced in soils, but they may be irrelevant to active orogens where high erosion rates on hillslopes are driven by landsliding. Still, until now relatively few studies have focused on measuring and explaining the variability of landslide grain size distributions. Here we present grain size distribution obtained by the grid-by-number method on 17 recent landslide deposits in Taiwan, and we compare it to the geometrical and physical properties of the landslides, such as their width, area, rock-type and strength, drop height and estimated depth. All landslides occurred in slightly metamorphosed sedimentary units, except two which occurred in younger unmetamorphosed shales, with rock strength expected to be 3 to 10 times weaker from their metamorphosed counterparts. We found that 4 deposits displayed a strong grain size segregation on their deposit with grains at the toe (downslope) of the deposit 3 to 10 times coarser than the one at the apex. In 3 cases, we could also measure the grain size distribution inside the landslides that presented percentiles 3 to 10 times finer than the surface of their deposits. Both observations could be due to either kinetic sieving or deposit reworking after the landslide failure but we could not explain why only some deposits had a strong segregation. Averaging this spatial variability we found the median grain size (D50) of the deposits to be strongly negatively correlated to drop height, scar width and depth. However, previous work suggests that regolith particlesvand bedrock blocks should become coarser with increasing depth (Cohen et al., 2010; Clarke and Burbank, 2011), opposite to our observation. Accounting for a model of regolith coarsening with depth, we found that the ratio of the original bedrock blocksize and the D50 was proportional to the potential energy of the landslide normalized to its bedrock strength. Thus the studied landslides agree well with the simple fragmentation model from Locat et al. (2006), even if it was calibrated on much larger and much stronger rock avalanches. This scaling may thus serve for future model of grain size transfer from hillslopes to river, trying to better understand landslide sediment evacuation and the coupling between hillslopes and river erosional dynamic. References: Clarke, B. A. and Burbank, D. W.: Quantifying bedrock-fracture patterns within the shallow subsurface: Implications for rock mass strength, bedrock landslides, and erodibility, Journal of Geophysical Research: Earth Surface, 116(F4), F04009, , 2011. Cohen, S., Willgoose, G. and Hancock, G.: The mARM3D spatially distributed soil evolution model: Three-dimensional model framework and analysis of hillslope and landform responses, Journal of Geophysical Research: Earth Surface, 115(F4), , 2010. Locat, P., Couture, R., Leroueil, S., Locat, J. and Jaboyedoff, M.: Fragmentation energy in rock avalanches, Canadian Geotechnical Journal, 43(8), 830–851, , 2006.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".