An Analytical Method for Assessing Recharge Using Groundwater Travel Time in Dupuit‐Forchheimer Aquifers
Bibliographic record
Abstract
An analytical solution to calculate the recharge of unconfined aquifers with Dupuit-Forchheimer type flow conditions is proposed. This solution is derived from an existing closed-form analytical solution initially developed to determine groundwater travel time when the recharge of the aquifer is known. This existing solution has been modified to determine recharge when groundwater travel time is known. An illustration is given with a field case example for the Bonifacio aquifer of the island of Corsica (France), in the Mediterranean. In this aquifer, previously established differences in groundwater residence time between two water samples were determined from anthropogenic atmospheric gas (chlorofluorocarbons and sulfur hexafluoride) measurements. The time difference is entered into the new analytical solution to determine recharge. The calculations yield a value of average recharge that agrees with the results obtained by several other methods that were presented in previous studies to assess the recharge of the Bonifacio aquifer. Also presented in this study is a sensitivity analysis of the new analytical solution, to quantify the influence of different parameters that control recharge: hydraulic conductivity, effective porosity and the groundwater travel time. This study illustrates how geochemical data can be combined with physical models to measure recharge. Such an approach could be adopted in other homogeneous aquifers worldwide that satisfy Dupuit-Forchheimer type flow conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".