Review of Laboratory Scale Models of Karst Aquifers: Approaches, Similitude, and Requirements
Bibliographic record
Abstract
This review focuses on investigations of groundwater flow and solute transport in karst aquifers through laboratory scale models (LSMs). In particular, LSMs have been used to generate new data under different hydraulic and contaminant transport conditions, testing of new approaches for site characterization, and providing new insights into flow and transport processes through complex karst aquifers. Due to the increasing need for LSMs to investigate a wide range of issues, associated with flow and solute migration karst aquifers this review attempts to classify, and introduce a framework for constructing a karst aquifer physical model that is more representative of field conditions. The LSMs are categorized into four groups: sand box, rock block, pipe/fracture network, and pipe-matrix coupling. These groups are compared and their advantages and disadvantages highlighted. The capabilities of such models have been extensively improved by new developments in experimental methods and measurement devices. Newer technologies such as 3D printing, computed tomography scanning, X-rays, nuclear magnetic resonance, novel geophysical techniques, and use of nanomaterials allow for greater flexibilities in conducting experiments. In order for LSMs to be representative of karst aquifers, a few requirements are introduced: (1) the ability to simulate heterogeneous distributions of karst hydraulic parameters, (2) establish Darcian and non-Darcian flow regimes and exchange between the matrix and conduits, (3) placement of adequate sampling points and intervals, and (4) achieving some degree of geometric, kinematic, and dynamic similitude to represent field 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".