Two-Dimensional Modeling of Tidally Influenced Ground Water Level Fluctuations
Bibliographic record
Abstract
A two-dimensional groundwater flow model was developed to evaluate potential groundwater remedial alternatives for a site located on a peninsula along the northwest coast of Washington State. The peninsula is flanked on either side by tidal estuaries. The model was developed using the saturated-unsaturated groundwater flow model MODFLOW-SURFACT99. Tidal fluctuations of up to approximately 4 meters (m) twice daily induce significant groundwater level fluctuations within the peninsula requiring that transient groundwater flow conditions be represented in the model to provide a reasonable assessment of alternative remedial designs. Challenges encountered during model calibration are presented and discussed. In particular, differing results were obtained using the pseudo-soil water retention functions implemented in MODFLOW-SURFACT99 versus the relationships of relative permeability versus water phase saturation and pressure head versus water phase saturation described by van Genuchten. Further, although borehole stratigraphy indicates the absence of a continuous low permeability layer in the shallow portion of the peninsula, the model calibration demonstrated that the numerous discontinuous silt and clay lenses that are observed throughout the deposit impart a confining to semi-confining effect on groundwater flow conditions at depth. Following model calibration, the model was applied to evaluate the performance of various groundwater remedial designs. The simulation results for a potential remedial alternative are presented.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".