Observed groundwater temperature response to recent climate change
Bibliographic record
Abstract
Abstract. Climate change is known to have a considerable influence on many components of the hydrological cycle. Yet, the implications for groundwater temperature, as an important driver for groundwater quality, thermal use and storage, are not yet comprehensively understood. Furthermore, few studies have examined the implications of climate-change-induced groundwater temperature rise for groundwater-dependent ecosystems. Here, we examine the coupling of atmospheric and groundwater warming by employing stochastic and deterministic models. Firstly, several decades of temperature time series are statistically analyzed with regard to climate regime shifts (CRSs) in the long-term mean. The observed increases in shallow groundwater temperatures can be associated with preceding positive shifts in regional surface air temperatures, which are in turn linked to global air temperature changes. The temperature data are also analyzed with an analytical solution to the conduction–advection heat transfer equation to investigate how subsurface heat transfer processes control the propagation of the surface temperature signals into the subsurface. In three of the four monitoring wells, the predicted groundwater temperature increases driven by the regime shifts at the surface boundary condition generally concur with the observed groundwater temperature trends. Due to complex interactions at the ground surface and the heat capacity of the unsaturated zone, the thermal signals from distinct changes in air temperature are damped and delayed in the subsurface, causing a more gradual increase in groundwater temperatures. These signals can have a significant impact on large-scale groundwater temperatures in shallow and economically important aquifers. These findings demonstrate that shallow groundwater temperatures have responded rapidly to recent climate change and thus provide insight into the vulnerability of aquifers and groundwater-dependent ecosystems to future climate change.
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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 | 0.000 | 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".