Numerically Simulated Groundwater Age Distributions within Complex Flow Systems and Discrete Fracture Networks
Bibliographic record
Abstract
Numerical simulations of mean groundwater age are presented for a variety of complex flow systems including heterogeneous aquifers and discretely-fractured porous rock. We apply the finite element models FLONET/TR2 (in the 2D vertical plane) and SALTFLOW (in 3D systems), using the standard advection-dispersion equation with an age source term. The age simulations are applied in a variety of contexts including defining capture zones for pumping wells, characterizing fractured rock aquifers, and for improved understanding of flow systems and geochemical evolution. Applications include real field sites and hypothetical conceptual models. Comparisons are also made with advective particle-tracking derived ages which are much faster to compute but do not include dispersive age mixing. Control of numerical (age) dispersion is critical, especially within discrete fracture networks where high age gradients can develop between the fractures and matrix. The presentation will highlight the broad applications of mean groundwater age simulations and will show how they can be useful for providing insight into hydrogeological systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".