Short‐Time Geodetic Determination of Aquifer Storage Coefficient in Taiwan
Bibliographic record
Abstract
Abstract Specific yield (Sy) and specific storage (Ss) are two hydrogeological parameters often estimated in a costly pumping test (hydraulic method). Pumping or a natural aquifer recession can cause gravity change and surface deformation, useful for Sy and Ss determination by the more economic geodetic method. From 2013 to 2017, over a few days we measured gravity changes at four sites and subsidence at one site in Taiwan by a FG5 gravimeter and a precision level to estimate Sy and Ss. Using short‐time gravity and level records avoids complicated logistic supports and temporal effects. The measured gravity changes are associated with the MODFLOW‐modeled groundwater depletion. We succeeded in estimating Sy at two sites and failed at the other two. One successful case uses rapid postrain declines of gravity and groundwater level. We did leveling only at one site, but here the 500‐min, continuous, submillimeter subsidence records result in a Ss consistent with the hydraulic result. Lessons on the failed cases of Sy are suggested to avoid disrupting factors in gravity surveys. A semiautomatic leveling procedure is proposed to maximize the chance for Ss determination. Our simulations show that gravity changes increase with Sy and decrease with initial hydraulic head and horizontal gravimeter‐pumping well distance, helping to predict if the gravity‐based method works at a site and to best plan a gravity survey. Drilling data show that the Sy values from the hydraulic and geodetic methods represent aquifer storage coefficients over different aquifer layers.
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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 | 0.001 | 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) | 0.001 | 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".