Fault Geometry, Slip Distribution, and Potential Triggering of the 2022 Mw 6.2 Deadly Afghanistan Earthquake Revealed from Geodetic and Weather Data
Bibliographic record
Abstract
Abstract The 22 June 2022 Mw 6.2 Khōst, Afghanistan, earthquake struck killing more than 1700 people and devastating the region. For studying this earthquake, we computed the coseismic deformation fields of the earthquake using the Sentinel-1 Terrain Observation with Progressive Scans Interferometric Synthetic Aperture Radar (InSAR). The InSAR results show that the maximum coseismic displacement in the satellite line of sight direction reaches up to 39 cm. We determined the geometric parameters of the fault and coseismic slip distribution from these InSAR measurements. The best-fitted fault model shows that the rupture occurred on a right-lateral strike-slip fault with a strike of 203.7° and a dip of 68°. The most slip is concentrated at a shallow depth within the upper 10 km with the maximum slip of ∼3 m at 2.5 km depth. The maximum slip produced by this earthquake is significantly larger than the slip produced by several other similar earthquakes with similar magnitudes, implying that the focused shallow slip is likely the reason for the significant damage in the earthquake. The heavy rainfall was recorded during the earthquake period, which resulted in complicated fringes in coseismic interferograms close to the earthquake in time. Because a positive spatial and temporal correlation with the earthquake occurrence can be seen, the rainfall may have potential contributions to the earthquake, which deserves additional analysis in future. Combined with the potential effects of the 2015 Mw 7.5 Hindu Kush deep-seated earthquake, the seismicity in Afghanistan is the result of the ongoing subduction of the Indian plate beneath the Eurasian plate along their west boundary.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".