Impact of Irrigation with Poor Quality Groundwater on Saskatchewan Soils
Bibliographic record
Abstract
Two irrigation sites near the rural communities of Donavon and Watrous, Saskatchewan were evaluated to determine the impact of irrigation with poor quality groundwater on soil and near-surface aquifer salinity. Prior to experimentation, the two sites had been irrigated with saline groundwater for six and seven years, respectively. Experimental work comprised both laboratory and field analysis. Laboratory experiments included monitoring chemical changes within the soil column profiles following application of fresh water and simulated aquifer water. The results indicated that although the level of chloride in the effluent initially increased, an equilibrium value was achieved following continued saline water application. In triplicate trials the rate of chloride ion removal was consistently lower than that predicted with a complete mixing leaching model, likely due to incomplete mixing of the applied and residual soil water. Field experiments included soil salinity surveys using a non-contacting electromagnetic terrain conductivity meter (EM 38) and saturated paste extracts (SPE) at the two groundwater irrigation sites to monitor salt accumulation in the soils between 1982 and 1988. Initial surveys indicated that salinity levels at the two sites were similar with higher salinity in the upper layers of soil, both inside and outside the irrigated circles. With the exception of the results from the deepest soil layer in which the SPE salinity exceeded EM 38 readings, no significant differences were observed between salinity measured from SPE and those computed from EM 38 readings at either the Donavon or Watrous 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".