Uncertainty in 1D Heat‐Flow Analysis to Estimate Groundwater Discharge to a Stream
Bibliographic record
Abstract
Temperature measurements have been used by a variety of researchers to gain insight into groundwater discharge patterns. However, much of this research has reduced the problem to heat and fluid flow in one dimension for ease of analysis. This approach is seemingly at odds with the goal of determining spatial variability in specific discharge, which implies that the temperature field will vary in more than one dimension. However, it is unclear how important the resulting discrepancies are in the context of determining groundwater discharge to surface water bodies. In this study, the importance of these variations is examined by testing two popular one-dimensional analytical solutions with stochastic models of heat and fluid flow in a two-dimensional porous medium. For cases with low degrees of heterogeneity in hydraulic conductivity, acceptable results are possible for specific discharges between 10(-7) and 10(-5) m/s. However, conduction into areas with specific discharges less than 10(-7) m/s from adjacent areas can lead to significant errors. In some of these cases, the one-dimensional solutions produced estimates of specific discharge of nearly 10(-6) m/s. This phenomenon is more likely in situations with greater degrees of heterogeneity.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".