Sustainable Crop Irrigation with Renewable Energy: A Case Study of Lethbridge County, Alberta
Bibliographic record
Abstract
The agriculture sector is a major contributor to the economy of Alberta, Canada, accounting for almost 2.8% of the total GDP. Considering its importance, implementing efficient and cost-effective irrigation systems is vital for promoting sustainable agriculture in semi-arid regions like Lethbridge County, Alberta, Canada. Although irrigation is primarily carried out using the Oldman River and its allied reservoirs, groundwater pumping becomes a supplementary necessity during periods of limited surface water availability or droughts. This research investigates the potential of renewable energy resources, such as wind and solar energy, to meet the energy requirements for crop irrigation. The study begins by identifying and calculating the water requirements for major crops in Lethbridge County, such as wheat and barley, using the United Nations Food and Agriculture Organization’s CROPWAT 8.0 software. Subsequently, energy calculations were conducted to meet the specific crop water demand through the design of a hybrid energy system using Homer Pro 3.16.2. A technoeconomic analysis of the renewable hybrid system has been carried out to demonstrate the efficiency and novelty of the proposed work. Outcomes revealed that the proposed system is both efficient and economical in fulfilling the crop water requirement through groundwater pumping, promoting sustainable agriculture, and helping to ensure food security in the region.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".