Improved Technologies and Management Practices in Irrigation—Implications for Water Savings in Southern Alberta
Bibliographic record
Abstract
Increased water use efficiency on irrigation farms is viewed as a source of water savings in semi-arid regions like southern Alberta where 71% of consumptive water use is for irrigation purposes. Alberta’s Water for Life strategy, the blueprint for long-term water planning, views increased water use efficiency as essential to improved water management. The present study examines the rate at which water use efficiencies have been, and plan to be increased by employing improved technologies and management practices. Findings from a survey of irrigators reveal that adopting improved technologies has been occurring at a decreasing rate and the rate is likely to continue to decrease in the future. The research indicates that the main reasons why irrigators adopt new technologies are to increase yield, and to save energy and labour costs, with saving water considered significantly less important. Reflecting that irrigators perceive financial constraints as one of the main impediments to invest in further improvements, our results indicate that the level of subsidies or commodity price increases required to convince them to make such investments are considerable. While further processing facilities in the area offer opportunities to grow specialty crops and thereby improve the financial position of irrigators, most specialty crops are high water users, not water savers. Improved water use efficiency could be advanced through greater promotion and education of improved water management practices.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".