Projected Changes in Hydrological Variables in the Agricultural Region of Alberta, Canada
Bibliographic record
Abstract
The responses of regional hydrological variables to climate change are of prime concern for agricultural water resources planning and management. Therefore, the seasonal (April–September) and annual (January–December) evolution of precipitation, temperature, evapotranspiration (ET), soil moisture (SM), deep aquifer recharge (DA), and water yield (WYLD) was investigated using established statistical techniques for the historical, near and far future (1983–2007: His, 2010–2034: NF, 2040–2064: FF) in the agricultural region of Alberta, Canada. Previously calibrated and validated agro-hydrological models (Soil and Water Assessment Tool) were used to generate these variables. Future changes were investigated under two representative concentration pathways, i.e., RCP 2.6 and RCP 8.5, projected by nine global climate models (GCM). Results revealed that Alberta had become warmer and drier during the His period. The future projection showed an increase in precipitation, SM, DA, and WYLD, in turn, indicated more water resources. Precipitation and temperature were projected to increase between 1 to 7% and 1.21 to 2.32 °C, respectively. Seasonal precipitation showed a higher trend magnitude than that of annual precipitation. The temperature generally had an increasing trend in the future with a maximum in the southern Alberta. Monthly average ET was likely to increase and decrease in the rising and falling limbs of the bell-shaped curve with the peak in July. A comparison of water demand from two land use types (dominant land use and barley) during the His period showed that water deficit existed in July and August. The results of this study could help in understanding anticipated changes in hydrological variables and decision-making regarding the regional agricultural water resources management.
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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".