Three-Dimensional Geostatistical Inverse Analyses of Transient Head and Temperature Data from a Long-Term Heat Tracer Test
Bibliographic record
Abstract
Two long-duration heat tracer tests have been conducted at the Narashino Site, Japan. A three-dimensional highly parameterized model is inverted with transient head and temperature data, individually and simultaneously, using the pilot point method to investigate the performance of different data sets in characterizing hydraulic conductivity (K) distribution. The performance results are evaluated qualitatively and quantitatively in various aspects, including K fields comparison, head and temperature matches for both model calibration and validation, identifiability and sensitivity analyses. Results of this study reveal that: 1) K fields obtained by inverting head data reveal finer details of heterogeneity, while small scale heterogeneity is smoothed when inverting temperature data; 2) combination of heat and temperature data improves the prediction of groundwater flow and heat transport in an independent heat tracer test; 3) increasing the data density is able to reveal more heterogeneity information and further improve the prediction performance; and 4) identifiability and sensitivity analyses suggest that head and temperature data contain unique and nonredundant information of the K heterogeneity. These results jointly suggest that the integration of transient head and temperature data shows promising potential in the delineating subsurface distribution of K and obtaining reliable predictions of head responses and heat plume migration.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".