Modeling of fast ground subsidence observed in southern Saskatchewan (Canada) during 2008–2011
Bibliographic record
Abstract
Abstract. Fast ground subsidence in southern Saskatchewan (Canada) between the City of Saskatoon and Rice Lake was observed with the RADARSAT-2 Interferometric Synthetic Aperture Radar (InSAR) during 2008–2011. We collected 23 ascending Multi-Look Fine 3 Far (MF3F) and 15 descending Standard 3 (S3) RADARSAT-2 images and performed time series analysis utilizing SBAS and MSBAS methodologies. We observed two well-defined circular regions located a few km apart and subsiding with the nearly constant rate of about 10 cm yr−1. MSBAS decomposition revealed presence of both vertical and horizontal ground displacements. For further analysis we selected two highly coherent interferograms spanning from November–December 2009 until April 2010 that due to particularly favorable ground conditions displayed superior coherence. We performed modeling and inversion assuming spherical and sill source models in order to determine the source location, depth and strength. The smallest residual of about 1 cm yr−1 was achieved with the sill model when both, ascending and descending, interferograms were used. This model suggested sources located at 1.3 and 1.2 km depth with radius of 1.0 and 1.3 km for eastern and western areas, respectively. The spherical model suggested slightly shallower sources located at 0.9 and 0.8 km. We could not precisely identify the cause of this deformation but the observed subsidence rate and source depth suggest mining related origin. Topographic changes produced by this subsidence rate over a long time may produce shallow groundwater redistribution and flooding of agricultural lands.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".