Thermal Imagery of Groundwater Seeps: Possibilities and Limitations
Bibliographic record
Abstract
Quantifying groundwater flow at seepage faces is crucial because seepage faces influence the hydroecology and water budgets of watersheds, lakes, rivers and oceans, and because measuring groundwater fluxes directly in aquifers is extremely difficult. Seepage faces provide a direct and measurable groundwater flux but there is no existing method to quantitatively image groundwater processes at this boundary. Our objective is to determine the possibilities and limitations of thermal imagery in quantifying groundwater discharge from discrete seeps. We developed a conceptual model of temperature below discrete seeps, observed 20 seeps spectacularly exposed in three dimensions at an unused limestone quarry and conducted field experiments to examine the role of diurnal changes and rock face heterogeneity on thermal imagery. The conceptual model suggests that convective air-water heat exchange driven by temperature differences is the dominant heat transfer mechanism. Thermal imagery is effective at locating and characterizing the flux of groundwater seeps. Areas of active groundwater flow and ice growth can be identified from thermal images in the winter, and seepage rates can be differentiated in the summer. However, the application of thermal imagery is limited by diverse factors including technical issues of image acquisition, diurnal changes in radiation and temperature, and rock face heterogeneity. Groundwater discharge rates could not be directly quantified from thermal imagery using our observations but our conceptual model and experiments suggest that thermal imagery could quantify groundwater discharge when there are large temperature differences, simple cliff faces, non-freezing conditions, and no solar radiation.
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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) | 0.001 | 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 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".