Climate Change Impacts on Groundwater Recharge in Cold and Humid Climates: Controlling Processes and Thresholds
Bibliographic record
Abstract
Long-term changes in precipitation and temperature indirectly impact aquifers through groundwater recharge (GWR). Although estimates of future GWR are needed for water resource management, they are uncertain in cold and humid climates due to the wide range in possible future climatic conditions. This work aims to (1) simulate the impacts of climate change on regional GWR for a cold and humid climate and (2) identify precipitation and temperature changes leading to significant long-term changes in GWR. Spatially distributed GWR is simulated in a case study for the southern Province of Quebec (Canada, 36,000 km2) using a water budget model. Climate scenarios from global climate models indicate warming temperatures and wetter conditions (RCP4.5 and RCP8.5; 1951–2100). The results show that annual precipitation increases of >+150 mm/yr or winter precipitation increases of >+25 mm will lead to significantly higher GWR. GWR is expected to decrease if the precipitation changes are lower than these thresholds. Significant GWR changes are produced only when the temperature change exceeds +2 °C. Temperature changes of >+4.5 °C limit the GWR increase to +30 mm/yr. This work provides useful insights into the regional assessment of future GWR in cold and humid climates, thus helping in planning decisions as climate change unfolds. The results are expected to be comparable to those in other regions with similar climates in post-glacial geological environments and future climate change conditions.
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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 | 0.000 | 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) | 0.001 | 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".