Exploring groundwater drought responsiveness in lowland post-glacial environments
Bibliographic record
Abstract
Abstract Groundwater drought response to meteorological forcing depends on initial hydrological conditions. This makes it difficult to characterise groundwater droughts and identify the drought vulnerability of aquifers. The objective is to increase the understanding of groundwater memory and response to meteorological forcing in lowland post-glacial environments. Eighty-one groundwater hydrographs are analysed, using the standardised groundwater level index (SGI) and the precipitation index. Memory and response times are assessed using auto- and cross-correlation functions. Response time is estimated by comparing two approaches: (1) the traditional use of the maximum cross-correlation, and (2) the alternative use of the cross-correlation slope. Results are interpreted for different hydrogeological settings. The analysis showed that sand aquifers have the longest memory and response times, particularly in confined settings where the memory could be over 4 years. Silts and tills have relatively short memories and response times, at less than 1 year, though median values for silt are higher than for unconfined sand aquifers. In this study, estimating response time using the correlation slope is superior at capturing the initial response time of groundwater to precipitation. However, the results showed that groundwater anomalies in lowland post-glacial environments are sometimes more influenced by climate teleconnections than concurrent forcing. This emphasises the need for a holistic approach for the characterisation and projection of groundwater drought, as it develops in simultaneous response to meteorological forcing at different timescales.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.001 |
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 teacher head, 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".