Statistical characteristics of aquitard hydraulic conductivity, specific storage and porosity
Bibliographic record
Abstract
• Laboratory experiments tend to result in lower aquitard K and higher aquitard S s . • Elastic S s is about one order of magnitude lower than inelastic S s. • For ϕ below 0.25, aquitard K tends to increase with ϕ and decrease vice versa. • Inelastic S s generally corresponds to ϕ > 0.37 and elastic S s to ϕ < 0.37. • ϕ outperforms other factors in predicting S s and is significant for predicting K. Aquitard hydraulic conductivity ( K ), specific storage ( S s ) and porosity ( ϕ ) are critical to the modeling of flow and mass and heat transport in groundwater systems, yet comprehensive insights into their statistical characteristics remain limited. This study compiles 456 K values from 47 studies, 202 S s values from 49 studies and 239 ϕ values from 18 studies, followed by rigorous statistical analysis of aquitard K , S s and ϕ with dependence on the features of test method, lithology and burial depth. Additionally, the interrelationships among K , S s and ϕ are analyzed. A predictive model for aquitard K and S s is developed utilizing the random forest (RF) approach. The statistical findings unearth that laboratory experiments tend to yield lower K while higher S s , particularly when burial depths are less than 50 m. Clay, silt clay, and glacial till exhibit comparable K values, in contrast to significantly lower K values observed in shale formations. Aquitard K , S s , and ϕ exhibit depth-decaying characteristics. Between two adjacent depth intervals, 0 – 50 m, 50 – 150 m and >150 m, there is nearly an order of magnitude difference in either K or S s . Aquitard K tends to increase with ϕ when ϕ is below 0.25 and decreases vice versa. This phenomenon is probably attributed to the significant amount of immobile-bound water adhering to clayey particles within the aquitard with a high ϕ value, which reduces the pore space available for water flow. Elastic S s , which indicates recoverable aquitard groundwater depletion, is about one order of magnitude lower than inelastic S s , which indicates permanent aquitard groundwater depletion, implying that the majority of groundwater depletion from aquitards under long-term groundwater exploitation is non-recoverable. The RF-based predictive model indicates that ϕ is a highly important feature for predicting K and outperforms lithology, test method and burial depth in predicting S s . The statistical findings of this study present a valuable basis for aquitard hydraulic parameters.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".