Triggering mechanism of long-distance flow-type landslides caused by 2018 Sulawesi Earthquake, Indonesia
Bibliographic record
Abstract
On 28 September 2018, the Mw 7.5 Sulawesi earthquake occurred in Indonesia, triggering long-distance flow-type landslides on very gentle slopes in and around Palu City. In order to investigate the triggering mechanism of these landslides, this study firstly compiled the field investigations that have been conducted since immediately after the earthquake and a soil profile of the landslide areas. Secondly, a groundwater flow analysis was carried out for the landslide in Petobo on the basis of the estimated soil cross-section. The results showed that, prior to the 2018 earthquake, there was confined groundwater with a water pressure of 40–60 kPa above what would be expected from the hydrostatic conditions in the flow zone of the landslide area. Finally, a simplified liquefaction analysis was performed using the groundwater pressure obtained by the groundwater flow analysis. The results indicated that, although the flow zone in the landslide area consisted of subsoils, including a relatively dense silty sand layer, it is likely that the significant liquefaction that occurred during the 2018 earthquake was due to the presence of confined groundwater. Furthermore, the authors concluded that the liquefaction probably contributed to the prolonged upward flow of large quantities of confined groundwater from aquifers located more than 20 m in depth below the ground surface, which resulted in a long-distance flow-type landslide by muddying the surface layer. It was also shown that the presence of an irrigation channel just above the landslide areas on the eastern side of Palu Valley had little effect on the sequence of landslide mechanism.
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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".