Multi-scale integrated characterization of heterogeneous hydraulic and thermal properties of a deltaic aquifer
Bibliographic record
Abstract
Historically, heat and temperature observations have been occasionally used to help understand aquifer systems or constrain numerical flow models. However, the development of fiber optics (FO) as part of the Distributed Temperature Sensing (DTS) technology has spun a renewed interest in the use of heat as a groundwater tracer. Recent studies have shown the possibility to carry out an active heat tracer test using fiber optics and heating cables installed by direct push and to invert the resulting thermal responses to estimate a vertical profile of groundwater fluxes. However, a better understanding of how FO-DTS results compare to other aquifer characterization methods is needed to guide its future application and integration into a practical workflow. The objective of this study was thus to compare the information provided by FO-DTS with other direct and indirect measurements used to characterize the heterogeneity of granular aquifers at multiple scales. The multiscale integrated characterization was carried out at a heterogeneous deltaic aquifer located north of Quebec City, Canada. This aquifer has been the object of a complete hydrogeological characterization and thus provides a wide range of existing data against which the acquired data can be compared. This communication will focus on the multiscale methodology for the granular aquifer characterization including FO-DTS measurements. Based on an existing numerical hydrogeological model, three sites with a range of horizontal groundwater fluxes were selected for active FO-DTS heat tracer experiments. At one of the sites, direct push monitoring wells were also installed downstream to measure the hydraulic conductivity of the hydrofacies and the arrival of the thermal front from the heat tracer test. A previous study established a relationship between the hydrofacies of the deltaic aquifer to cone penetration test (CPT) response. As such, each FO cable and monitoring well direct-push installation was preceded by a co-located CPT. Soil cores were also taken for laboratory measurements of hydraulic and thermal properties. The vertical profiles of groundwater fluxes from FO-DTS were found to correlate well with the relative magnitude of permeability of the hydrofacies identified with CPT profiles. FO-DTS could thus provide a qualitative or quantitative proxy for hydraulic conductivity and allow the recognition of hydrofacies at a fine scale. At the aquifer scale, the total flux measured by FO-DTS can also be compared to fluxes obtained from numerical models and thus provide a constraint to validate models. Overall, this study shows that not only does FO-DTS provide coherent results with other characterization methods, but it also adds the key measurement of groundwater flux that cannot be easily obtained by other means. FO-DTS thus has the potential to become a significant addition to existing characterization methods for granular aquifers.
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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) | 0.000 | 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".