Modeling of a Contaminant Plume in a Tidally Influenced River Using Domenico’s Equation
Bibliographic record
Abstract
Currently, the mathematical code Modflow is widely used to simulate groundwater flow in aquifers. Due to the ease which exists today to create mathematical models through Modflow visual Interfaces, it is possible to obtain contamiant transport results which may not have much support, especially when simulating the transport of contaminants with little groundwater flow information. Domenico’s equation is an analytical solution for transport of contaminants in groundwater that can be used when not much groundwater flow information exists. The objective of this study is to model, using Domenico’s equation, a groundwater contaminant plume that discharges into a tidally influenced river. The study area was a wood treatment facility located on the bank of a river which is influenced by tides. Previous studies have found the presence of creosote in the subsurface and the formation of a groundwater plume that apparently discharges into the river. Domenico’s equation was selected to model this site because of the limited piezometric data available at the site to properly simulate the daily hydraulic gradient inversion due to the river tides. Domenico’s equation was successfully used to model this plume and reproduce the field distribution of naphthalene, benzene and 1-methyl-naphthalene. Two sources 40 minland had to be defined to properly simulate the plume behavior. It was determined through modeling that biodegradation plays an important role on the plume’s behavior. These were key issues in the conceptual model understanding of the plume at this site.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".