Integrated Hydrological and Geophysical Characterisation of Surface and Subsurface Water Contamination at Abandoned Metal Mines
Bibliographic record
Abstract
The mining and processing of metal ores in the UK has left a legacy of environmental degradation, and abandoned metal mines still pose a significant threat to terrestrial and fluvial environments. Flow gauging, water quality and geophysics were combined in an integrated assessment of surface and subsurface hydrological contamination at Esgair Mwyn, an abandoned mine in Ceredigion, Wales. Heavy metals discharged from the site are polluting downstream watercourses, leading to widespread Environmental Quality Standards (EQS) compliance failures. Through salt water dilution gauging and water quality sampling, a daily efflux of 876 g of heavy metals was calculated, with contaminant mobilisation occurring mainly in two primary surface streams draining an exposed tailings heap. Electrical resistivity tomography subsurface imaging found a seepage plane within the tailings lagoon wall, whilst the main tailings heap became increasingly saturated with depth. A large adjacent field also had a high potential to convey pollutants in solution, yet its morphological characteristics have limited transmission, as the area acts as a passive treatment type system. With remediation of already polluted water both difficult and expensive, this approach provides a cost-effective way to identify the origins and pathways of contaminants, informing mitigation strategies focussed on containment. Esgair Mwyn is not an isolated case, as abandoned metal mines release at least 860 t of heavy metals annually into UK water bodies. These techniques could reduce or prevent abandoned metal mine hydrological pollution for decades to come, and enable associated UK water bodies to comply with future water quality standards.
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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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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 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".