Groundwater flow and transport model of the Red River/Interlake area in Southern Manitoba
Bibliographic record
Abstract
A regional flow and solute transport model was constructed for two bedrock aquifers in Southern Manitoba. The "Carbonate Aquifer" is located in the fractured, more permeable region of the outcropping carbonate rocks and is used for rural domestic, industrial, irrigation and agricultural purposes. The "Sandstone Aquifer" is located within the interbedded sandstones and shales of the Winnipeg Formation and is utilized for rural domestic purposes. Transmissivity measurements were obtained for both aquifers from pump and specific capacity tests. It was determined that the transmissivity in m2/s followed a natural log normal distribution for both aquifers with a mean of -7.2 and -8.0 for the Carbonate and Sandstone Aquifers, respectively. The variograms were calculated using an estimator developed by Li and Lake (1994). Fractal nature was not evident in the variogram of either aquifer. Bayesian Updating was used to generate heterogeneous hydraulic conductivity fields. For the Carbonate Aquifer this field was successfully used to assign hydraulic conductivity, however due to lack of measurements the hydraulic conductivity for the Sandstone Aquifer was assigned through zonation. The resulting flow model had a RMS error of 7.49 m. The plot of computed versus observed equivalent freshwater heads showed significant correlation. Linear regression was conducted and the slope and intercept compared against the desired values of 1.0 and 0.0, respectively, using the t-test. For the transport model, the RMS error was 2.9 g/L, however the plot of computed versus observed concentrations had a slope significantly different than one. The model was used to evaluate several water resources engineering applications. The model runs examining sustainability showed that 1 g/L contour moved slightly northeast in the Carbonate Aquifer and only had slight movement in the Sandstone Aquifer.
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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 | 0.000 | 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".