Climate change impacts on the temperature and magnitude of groundwater discharge from shallow, unconfined aquifers
Bibliographic record
Abstract
Abstract Cold groundwater discharge to streams and rivers can provide critical thermal refuge for threatened salmonids and other aquatic species during warm summer periods. Climate change may influence groundwater temperature and flow rates, which may in turn impact riverine ecosystems. This study evaluates the potential impact of climate change on the timing, magnitude, and temperature of groundwater discharge from small, unconfined aquifers that undergo seasonal freezing and thawing. Seven downscaled climate scenarios for 2046–2065 were utilized to drive surficial water and energy balance models (HELP3 and ForHyM2) to obtain future projections for daily ground surface temperature and groundwater recharge. These future surface conditions were then applied as boundary conditions to drive subsurface simulations of variably saturated groundwater flow and energy transport. The subsurface simulations were performed with the U.S. Geological Survey finite element model SUTRA that was recently modified to include the dynamic freeze‐thaw process. The SUTRA simulations indicate a potential rise in the magnitude (up to 34%) and temperature (up to 3.6°C) of groundwater discharge to the adjacent river during the summer months due to projected increases in air temperature and precipitation. The thermal response of groundwater to climate change is shown to be strongly dependent on the aquifer dimensions. Thus, the simulations demonstrate that the thermal sensitivity of aquifers and baseflow‐dominated streams to decadal climate change may be more complex than previously thought. Furthermore, the results indicate that the probability of exceeding critical temperature thresholds within groundwater‐sourced thermal refugia may significantly increase under the most extreme climate scenarios.
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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 | 0.000 |
| 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) | 0.001 | 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".