The impact of our warming climate on global groundwater temperatures
Bibliographic record
Abstract
Groundwater, the largest reservoir of unfrozen freshwater on Earth, plays a crucial role in supporting life and ecosystems. Its thermal regimes influence various environmental processes, impacting groundwater-dependent ecosystems, geothermal potential, and groundwater quality. Despite its significance, little is known about how groundwater responds to surface warming across spatial and temporal scales. Here we present a comprehensive analysis of global groundwater temperature patterns, utilizing the latest CMIP6 scenarios.In this study we developed the first global model of groundwater temperature patterns, combining analytical solutions to conductive heat transport with high-resolution maps of ground thermal diffusivity and geothermal gradient. This model, validated with over 8,000 groundwater temperature measurements, allows users to estimate present and future temperature depth profiles globally. Past trends show a median global groundwater temperature increase of 0.3 °C over the last two decades. When simulating projected groundwater temperatures globally, our model reveals an average warming of 2.2°C (SSP 245) to 3.8°C (SSP 585) between 2000 and 2100 at the depth of the water table. Regional variations are substantial due to climate change and water table depth variability, with mountainous regions exhibiting the lowest warming rates. These distinct regional variations emphasize important thermal controls and the need for localized analysis.Our work sheds light on the importance of understanding groundwater warming patterns, identifying 'hot spots' that may pose risks to both ecosystems and human well-being. In this study we also offer a specific focus on Europe, providing averages to enhance regional relevance and address emerging challenges in groundwater quality and habitat preservation.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".