Simulated response of groundwater to predicted recharge in a semi-arid region using a scenario of modelled climate change
Bibliographic record
Abstract
Groundwater systems in arid regions will be particularly sensitive to climate change owing to the strong dependence of rates of evapotranspiration on temperature, and shifts in the precipitation regimes. In agricultural areas, such changes in climate may require increased irrigation, putting stress on existing water supplies. In this study, a regional-scale numerical groundwater model was developed for the Oliver region of the south Okanagan, British Columbia, Canada, to simulate the impacts of future predicted climate change on groundwater. In future time periods (the 2050s and 2080s), the most noticeable change in the water budget is the increased contribution of recharge to the annual water budget, estimated at 1.2% (2050s) and 1.4% (2080s) of the total annual budget relative to the current conditions. This increase is related primarily to increases to irrigation return flow resulting from higher irrigation needs under warmer temperatures and a longer growing season. Increases in recharge and irrigation return flow will result in higher water tables with future climate conditions, particularly in the irrigation districts. Median value increases in groundwater level of up to 0.7 m by the 2080s are estimated.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".