Integrated analysis of Hashtgerd plain deformation, using Sentinel-1 SAR, geological and hydrological data
Bibliographic record
Abstract
Due to its proximity to Tehran, the Hashtgerd catchment in Iran is an important region that has experienced alarming subsidence rates in recent years. This study estimated the ground surface deformation in the Hashtgerd plain between 2015 and 2020 using Sentinel-1 SAR data and InSAR technique. The average LOS displacement of the ascending and descending tracks was - 23 cm/year and - 22 cm/year, respectively. The central area of the plain experienced the greatest vertical subsidence, with a more than - 100 cm cumulative displacement. The Karaj-Qazvin railway and highway that pass through this area have been damaged by subsidence, according to an analysis of profiles drawn along the transportation lines. The southern sections of Hashtgerd city have experienced a total displacement of - 30 cm/year over the course of about 6 years. The relationship between changes in groundwater level and subsidence rate in this region was examined using piezometer and precipitation data. Geoelectric sections and piezometric well logs were also utilized to investigate the geological characteristics of the Hashtgerd aquifer. According to the findings, the leading causes of subsidence were uncontrolled groundwater abstraction. This research highlights the need to comprehend the spatial distribution of confined aquifers and their effect on subsidence, which can aid in the development of a suitable management strategy to restore these aquifers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".