Driving processes of long-term large scale groundwater recharge in cold and humid climates
Bibliographic record
Abstract
Large scale and long-term estimates of groundwater recharge (GWR) are strategic for assessing the relative impacts of climate change and land cover (LC) change on groundwater resources. This is especially true in cold and humid climates where global change has a high disrupting potential. Therefore, this work aims to determine the driving processes of long-term and large-scale GWR in cold and humid climates. Using a parsimonious model, GWR was simulated in the cold and humid region of southern Quebec, Canada (35 800 km2) over the past decades (1961-2017) and for potential future conditions (12 scenarios, 1951-2100). Constant and time-variant LC were used, with a monthly time step and a 500 m x 500 m spatial resolution. The datasets and model are open source. The simulated past and future results showed the importance of seasonality for GWR and the key role of annual temperature in the spatial distribution of GWR rates. They highlighted the high responsiveness of the cold and humid region hydrology to long-term interannual climate variability and the importance of simulating the snow and freezing processes when estimating GWR in these climates. In the future, warmer temperatures during the cold months (less precipitation as snow, earlier snowpack melting) led to more liquid water available when the vegetation was dormant, leading to higher GWR. Warmer temperatures during the rest of the year extended the growing period and increased plant water uptake, directly decreasing the water available for GWR. The direction of the annual changes in GWR thus depended on whether the increase during the cold months could offset the decrease during the rest of the year. The sensitivity of GWR to climate change increased with the increase in LC change intensity. The spatial distribution of LC changes was identified as another driver of GWR change as afforestation took place on agricultural areas, located on the flattest and clayey areas, thus reducing the GWR rates for forested area over time. This work called for a more systematic inclusion of LC changes in long-term groundwater resource simulation and proposes a computationally-affordable methodology to tackle it.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".