Prediction of groundwater characteristics in forested and harvested basins during spring snowmelt using a topographic index
Bibliographic record
Abstract
Abstract Consistent relationships between groundwater conditions and topographic properties in small drainage basins would assist the study and modelling of basin hydrology and hydrochemistry. Hydrochemical simulation using topographically based models would benefit in particular from the linkage of groundwater residence times to topographic indices, such as the ln(a / tan β) index of Beven and Kirkby. Hypothesized associations between this index and groundwater characteristics were tested during the spring 2000 snowmelt in two sub‐basins in the Turkey Lakes Watershed near Sault Ste Marie, ON. One sub‐basin is in mature hardwood forest, and the other was clearcut in the fall of 1997. Piezometric surface elevations were monitored in each sub‐basin throughout the melt, and the topographic index value for each piezometer was determined. The δ18O signatures of input water and groundwater were also measured. Mean groundwater residence times were obtained using the exponential system response function, which generally produced good fits to the observed groundwater δ18O time series in both sub‐basins. There were significant contrasts in groundwater conditions between the sub‐basins. The forested sub‐basin exhibited higher and more temporally variable piezometric surface elevations and a greater contrast between δ18O signatures and water residence times in shallow versus deeper groundwater relative to the harvested sub‐basin. Patterns of groundwater residence times in the sub‐basins were supported by pre‐harvest groundwater chemistry; however, data from the two sub‐basins largely failed to support the hypothesized relationships between groundwater conditions and topographic index values. Methodological limitations that may have precluded a more rigorous test of the hypotheses are reviewed, and the potential for using groundwater residence times to evaluate the impacts of forest harvesting on basin hydrochemistry is briefly discussed. Copyright © 2001 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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 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".