Hydromorphological and Hydrogeological Assessment of Liquefaction Vulnerability in Central Sulawesi, Indonesia
Bibliographic record
Abstract
The earthquake disaster that struck the regions of Palu, Sigi, and Donggala on September 28, 2018, instigated liquefaction in Petobo and its surrounding areas.This study employs a hydrogeological approach, supplemented by geospatial analysis, to comprehensively evaluate the vulnerability to liquefaction in these regions, focusing specifically on hydromorphological and hydrogeological parameters such as phreatic and aquifer characteristics.Data were collected from 25 randomly selected observational dug wells in the Petobo area and its surroundings, and the analysis was facilitated by the Arc View Gis 3.3 program and satellite imagery.Based on the measurement results in 25 observation dug wells, the depth of the phreatic level was found to be shallow, at 2.25 meters from the ground surface, and its fluctuations were low, at 0.67 meters.The permeability was relatively high, averaging 49.18 meters/day.The regions experienced liquefaction avalanches in areas with a slope of less than 4%, which led to an increase in groundwater flow velocity and an elevation in the phreatic level between 2.0 and 2.5 meters.Hydrogeologically, these areas are located within the Alluvium and Pakuli formations, characterized by sand, clay, sand-clay, sand-gravel, and schist lithologies.In conclusion, the study reveals that Petobo and its surrounding areas exhibit a high vulnerability to liquefaction, ascribed to the shallow phreatic levels and high aquifer parameters observed in the alluvial plains.These findings underscore the need for careful consideration of these factors in future planning and disaster mitigation strategies in regions with similar geological and hydrogeological characteristics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".