Electrical characterization of non‐Fickian transport in groundwater and hyporheic systems
Bibliographic record
Abstract
Recent work indicates that processes controlling solute mass transfer between mobile and less mobile domains in porous media may be quantified by combining electrical geophysical methods and electrically conductive tracers. Whereas direct geochemical measurements of solute preferentially sample the mobile domain, electrical geophysical methods are sensitive to changes in bulk electrical conductivity (bulk EC) and therefore sample EC in both the mobile and immobile domains. Consequently, the conductivity difference between direct geochemical samples and remotely sensed electrical geophysical measurements may provide an indication of mass transfer rates and mobile and immobile porosities in situ. Here we present (1) an overview of a theoretical framework for determining parameters controlling mass transfer with electrical resistivity in situ; (2) a review of a case study estimating mass transfer processes in a pilot‐scale aquifer storage recovery test; and (3) an example application of this method for estimating mass transfer in watershed settings between streams and the hyporheic corridor. We demonstrate that numerical simulations of electrical resistivity studies of the stream/hyporheic boundary can help constrain volumes and rates of mobile‐immobile mass transfer. We conclude with directions for future research applying electrical geophysics to understand field‐scale transport in aquifer and fluvial systems subject to rate‐limited mass transfer.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".