Monitoring of land surface subsidence using persistent scatterer interferometry techniques and ground truth data in arid and semi-arid regions, the case of Remah, UAE
Bibliographic record
Abstract
The United Arab Emirates (UAE) is located in an arid desert climate with very limited water resources and scarce rainfall. Along with the fast development of the country, the water demand for agriculture, industrial, and domestic purposes increased and led to diminishing groundwater resources. In this study, we explore the land surface deformations due to groundwater overexploitation in the agricultural area of Remah by analyzing Sentinel-1 data between 2015 and 2019 with the novel Parallelized-Persistent Scatterer Interferometry (P-PSI) technique. The detected land surface deformations have been correlated to the recorded groundwater levels at nearby water wells. This study detected land surface deformations in a form of an extensive subsidence bowl (with 28.5 km in diameter) with a maximum subsidence rate of 40 mm/year and a standard deviation within the bowl of less than 2 mm/year. The detected subsidence was associated with a 12 m drop in the water table level within the study area. The Persistent Scatterers with the highest deformations rate were spatially correlated with the depression cone of the groundwater level. These findings provide useful insights in understanding the groundwater regime of the area and have an important role in assessing regional hazards and driving mitigation measures towards managing uncontrolled groundwater overexploitation for sustainable management of groundwater resources.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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 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".