Spatial and Seasonal Variations of Water and Salt Movement in the Vadose Zone at Salt-Impacted Sites
Bibliographic record
Abstract
Oilfield-produced brine is a major source of salt contamination in soil and groundwater. Salt transport in the upper soil layers is controlled by the atmospheric interactions via infiltration of meteoritic water. In lower layers, it is controlled by fluctuations in the groundwater table, which are also linked to atmospheric interactions via groundwater recharge. Therefore, climate is an important factor in the movement of contaminants in the unsaturated zone. A one-dimensional variably saturated flow and transport model with soil atmospheric boundary conditions was used to estimate the effect of climate type and soil texture on soil water and salt dynamics in variably saturated soils. Numerical simulations were run with Hydrus-1D, using daily climate data. Simulations were run for nine-year climate datasets for different ecoclimatic locations in Alberta, Canada. Results indicated that coarse-grained materials are good evaporation barriers, resulting in water gain conditions at the ground surface, irrespective of the climate type. However, the quantity of water gain and associated advective fluxes are a function of climate. Results also indicated that flow and transport in fine-textured soils is more dependent on the climate type. For fine-grained soils in arid climatic conditions, net water loss at the ground surface and upward migration of salt can be expected. For wetter climates, the upward migration of salt is less probable.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".