Influence of past and future atmospheric and oceanic climate change on groundwater levels, recharge, discharge, and salinity
Bibliographic record
Abstract
Atmospheric climate change in cold regions can impact groundwater resources through alterations to snow-rain partitioning, mid-winter thaws, and evapotranspiration. Also, sea-level rise can drive elevated coastal water tables and saltwater intrusion, which can deleteriously impact coastal groundwater resources and coastal infrastructure. We investigate these processes in the coastal province of Nova Scotia, Canada, where 40% of the population relies on vulnerable private wells. We consider impacts of past climate change by conducting statistical analyses of hydrometeorological data and find that late-summer significant negative trends are apparent in net precipitation, groundwater levels, and groundwater discharge (baseflow). To assess the impacts of future climate change we are developing province-wide coastal groundwater vulnerability maps (salinization and water table rise) based on a coastal groundwater analytical solution parameterized and forced with geospatial data. We are also using downscaled climate projections to drive a physically-based hydrologic model to investigate how groundwater recharge may respond to changing temperature and precipitation in different hydrologic response units. Our preliminary results provide critical insights into the impacts of climate change on groundwater resources and lay the foundation for better risk identification to underpin sustainable groundwater management.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".