Assessment of the Potential Impacts of Climate Change on the Hydrology and Canola Yield Using the DRAINMOD Model
Bibliographic record
Abstract
Highlights Total precipitation and average temperature are projected to increase in the Interlake region of Manitoba. DRAINMOD model results suggest that controlled drainage (CD) would significantly decrease subsurface drainage. Due to dry stress, canola yield is projected to decrease under free drainage (FD) and controlled drainage (CD). Simulation results suggest that capturing, storing, and reusing drainage water could be an adaptive and mitigative strategy for climate change impacts. Abstract. Climate change is a major concern for agricultural production regions like the Canadian Prairies. Therefore, understanding the hydrologic and crop yield response to climate change is important to developing adaptative and mitigative strategies. Downscaled climate model projections from two GCMs for historical (1981-2010), midcentury (2041-2070), and late-century (2071–2100) periods under three representative concentration pathways (RCP2.6, RCP4.5, and RCP 8.5) were used as climate inputs to drive a calibrated and validated DRAINMOD model under two water management scenarios: free drainage (FD) and controlled drainage (CD). Field data, including water table depth, was collected for two canola growing seasons at the PESAI (Prairies East Sustainable Agriculture Initiative) research site in Arborg, Manitoba, Canada. The model was calibrated and validated using the 2019 and 2020 water table depth. The projected changes in the climatic variables showed a slight increase in the mean annual precipitation and the mean temperature across the seasons. DRAINMOD simulation results suggest that CD would significantly decrease subsurface drainage, while water loss through evapotranspiration (ET) and surface runoff are projected to increase considerably under CD and FD. Furthermore, results showed that the relative canola yield would decrease under FD and CD. Stressor analysis showed that canola yield reduction was driven by dry stress due to the projected temperature rise, which outweighs the slight increase in precipitation. Simulation results suggest that the capture, storage, and reuse of drainage water could be an adaptive and mitigative strategy to address the predicted impacts. Keywords: Canola yield, Climate change, DRAINMOD model, Subsurface drainage.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".